Speakers

Saif Addin Ellafi is a software developer at John Snow Labs, where he’s the main contributor to Spark NLP. A data scientist, forever student, and an extreme sports and gaming enthusiast, Saif has wide experience in problem solving and quality assurance in the banking and finance industry.

Sarah Aerni is a director of data science at Salesforce Einstein, where she works to democratize machine learning by building products that allow customers to deploy predictive apps in a few short clicks. Her team builds automated machine learning pipelines and products like Einstein Prediction Builder. Previously, she led teams in healthcare and life sciences at Pivotal building models for customers. She is a recovering academic and entrepreneur, with a PhD in biomedical informatics from Stanford University and a passion for building diverse teams, education, and exploration.

Jaipaul Agonus is a director in the Market Regulation Technology Department at FINRA. Jaipaul is a big data engineering leader with nearly 18 years of IT industry experience, specializing in big data analytics and cloud-based solutions. He’s currently involved in building next-generation big data market analytic platforms with machine learning, advanced visualization, and contextual access across applications.

Shradha Agrawal is a data scientist at Adobe in San Jose. She holds a master’s degree in computer science with a focus on AI and machine learning from the University of California, San Diego. She is the author of a number of papers and patent applications.

Sridhar Alla is cofounder and CTO at BlueWhale, which brings together the worlds of big data and artificial intelligence to provide comprehensive solutions to meet the business needs of organizations of all sizes. He and his team are cloud and tool agnostic and strive to embed themselves into the workstream to provide strategic and technical assistance, with solutions such as predictive modeling and analytics, capacity planning, forecasting, anomaly detection, advanced NLP, chatbot development, SAS to Python migration, and deep learning-based model building and operationalization. Sridhar is also the author of three books and an avid presenter at conferences including Strata, Hadoop World, Spark Summit and others.

Josh Alwitt is responsible for leadership and culture at Publicis Sapient, where he cocreates a culture that enables people to thrive at work through living the organization’s shared purpose and values and is also responsible for executive development, leading a neuroscience-based leadership development program, and coaching the C suite, senior executives, and client account leaders. Previously, Josh created the Talent Development function at Sapient, which included learning and development, performance management, career development, succession planning, leadership development, and integrated talent systems. Before his organizational development work, Josh was a technology consultant for 20 years, leading large custom software implementations in a variety of client industries.

Jesse Anderson is a data engineer, creative engineer, and managing director of the Big Data Institute. Jesse trains employees on big data—including cutting-edge technology like Apache Kafka, Apache Hadoop, and Apache Spark. He’s taught thousands of students at companies ranging from startups to Fortune 100 companies the skills to become data engineers. He’s widely regarded as an expert in the field and recognized for his novel teaching practices. Jesse is published by O’Reilly and Pragmatic Programmers and has been covered in such prestigious media outlets as the Wall Street Journal, CNN, BBC, NPR, Engadget, and Wired. You can learn more about Jesse at Jesse-Anderson.com.

Zachery Anderson is the chief analytics officer and senior vice president at Electronic Arts (EA), the world’s largest video game company, where he’s responsible for leading consumer insights, UX research, data science, studio analytics, and marketing analytics. His team uses in-game behavioral data, traditional consumer research, lab work, and online advertising data to provoke and inspire EA’s development and marketing teams to think and act “player first.” Previously, Zachery was head of consulting and modeling for the PIN Group at J.D. Power and Associates, corporate economist at Nissan North America, and economist at investment company Fremont Group. Zachery’s work has been highlighted in the Harvard Business Review and MIT Sloan Management Review and has won many awards, including the INFORMS Marketing Science Practice Prize. While at Nissan, he was recognized by the US Federal Reserve for the best industry forecast. He’s a member of the University of California Master of Science in Business Analytics Industry Advisory Board. Zachery holds an undergraduate degree in political science and communications from Southern Illinois University and a graduate degree in economics and political science from UCLA, where he studied game theory with Nobel Prize winner Lloyd Shapley.

Eva Nahari is director of product management at Cloudera, where she helps drive the future of distributed data processing and machine learning applications through Cloudera’s distribution of Hadoop and expedites the next generation of integrated search engines. Eva has been working with Java virtual machine technologies, SOA, cloud, and other enterprise middleware solutions for the past 15+ years. Previously, she was the developer of JRockit (the world’s fastest JVM) and productized Zing (the world’s only pauseless JVM) at Azul Systems. She also pioneered deterministic garbage collection and was awarded two patents on garbage collection heuristics and algorithms. In addition, she’s managed many technical partnerships, among them Sun, Intel, Dell, and Red Hat, as well as multicomponent software integration projects, including JRockit, Coherence, WebLogic, Zing, RHEL, and Cloudera Search. Eva holds an MSc in artificial intelligence and autonomous systems from the Royal Institute of Technology in Stockholm, Sweden.

June Andrews is a principal data scientist at GE, where she’s building a machine learning platform used for monitoring the health of airplanes and power plants around the world. Previously, she spearheaded the Data Trustworthiness and Signals Program at Pinterest aimed at creating a healthy data ecosystem for machine learning and led efforts at LinkedIn on growth, engagement, and social network analysis to increase economic opportunity for professionals. June holds degrees in applied mathematics, computer science, and electrical engineering from UC Berkeley and Cornell.

André Araujo is a principal solutions architect at Cloudera. An experienced consultant with a deep understanding of the Hadoop stack and its components and a methodical and keen troubleshooter who loves making things run faster, André is skilled across the entire Hadoop ecosystem and specializes in building high-performance, secure, robust, and scalable architectures to fit customers’ needs.

Tim Armstrong is an engineer at Cloudera, where he works on making Apache Impala faster and more robust via improvements to query execution and resource management. He holds a PhD focused on the intersection of high-performance computing and programming language implementation.

Shirya Arora works on the data engineering team for personalization at Netflix, which, among other things, delivers recommendations made for each user. The team is responsible for the data that goes into training and scoring of the various machine learning models that power the Netflix home page. They have been working on moving some of the company’s core datasets from being processed in a once-a-day daily batch ETL to being processed in near real time using Apache Flink. Previously, she helped build and architect the new generation of item setup at Walmart Labs, moving from batch processing to stream. They used Storm and Kafka to enable a microservices architecture that allows products to be updated near real time as opposed to once a day on the legacy framework.

Matvey Arye is a senior software engineer at TimescaleDB, where he works on performance, scalability, and query power. Mat has been working on data infrastructure in both academia and industry. He attended Stuyvesant and the Cooper Union and holds a PhD from Princeton. In his free time, Mat enjoys theater, travel, hiking, and skiing.

Kirstin Aschbacher is a data scientist, a licensed clinical psychologist with a specialty in behavioral medicine, an associate professor in cardiology at UCSF, and the data team lead on the Health eHeart (HeH)/Eureka Digital Research Platform. One of her passions is to bridge the worlds of behavior change and data science in order to transform health, and she enjoys finding creative ways to take knowledge from psychology, neuroscience, and biology and apply them to discover new insights in large datasets. At UCSF, she builds active partnerships with companies in the behavior change and lifestyle medicine space. Previously, she was a data scientist at Silicon Valley startup Jawbone, where she helped design, test, and analyze mini-interventions to help users make healthier behavior choices and lose weight. When she’s not at work, she enjoys being a mother to her two children, biking and dancing, and learning to speak Mandarin.

Jitender Aswani supports the infrastructure and security data engineering teams at Netflix. His team designs, builds, and deploys scalable big data architecture and solutions to enable business and operations teams to achieve consistent capacity, reliability, and security gains. Jitender is a lifelong student of smart data products and data science solutions that push organizations to make data-inspired decisions and adopt analytics-first approaches.

Shivnath Babu is the CTO at Unravel Data Systems and an adjunct professor of computer science at Duke University. His research focuses on ease of use and manageability of data-intensive systems, automated problem diagnosis, and cluster sizing for applications running on cloud platforms. Shivnath cofounded Unravel to solve the application management challenges that companies face when they adopt systems like Hadoop and Spark. Unravel originated from the Starfish platform built at Duke, which has been downloaded by over 100 companies. Shivnath has won a US National Science Foundation CAREER Award, three IBM Faculty Awards, and an HP Labs Innovation Research Award.

Kamil Bajda-Pawlikowski is a cofounder and CTO of the enterprise Presto company Starburst. Previously, Kamil was the chief architect at the Teradata Center for Hadoop in Boston, focusing on the open source SQL engine Presto, and the cofounder and chief software architect of Hadapt, the first SQL-on-Hadoop company (acquired by Teradata). Kamil began his journey with Hadoop and modern MPP SQL architectures about 10 years ago during a doctoral program at Yale University, where he co-invented HadoopDB, the original foundation of Hadapt’s technology. He holds an MS in computer science from Wroclaw University of Technology and both an MS and an MPhil in computer science from Yale University.

Ambal Balakrishnan is a digital segment lead for IBM Analytics within the Data Organization at IBM. A technology-focused product management/marketing leader with a strong track record of leading strategic growth, she leads digital transformation and growth of the Data Organization segment of the IBM Analytics portfolio by creating and bringing to market digital and SaaS product offerings. Previously, she was worldwide content marketing leader for systems hybrid cloud DevOps, where she managed content marketing strategy, digital content design, and production to drive business results, and worked on worldwide marketing and positioning of Cisco’s cloud and data center switching business. Ambal holds a master’s in computer science from Purdue University and an MBA in marketing, strategy, and entrepreneurship from the Wharton School at the University of Pennsylvania.

Satheesh Bandaram is an executive director for big data and data virtualization within the R&D organization at IBM. Key offerings include IBM Db2 BigSQL, IBM BigReplicate, and the newly launched data virtualization technology that is available for private and public cloud deployments using IBM Cloud Private for Data.

Burcu Baran is a senior data scientist at LinkedIn. Burcu is passionate about bringing mathematical solutions to business problems using machine learning techniques. Previously, she worked on predicting modeling at a B2B business intelligence company and was a postdoc in the Mathematics Departments at both Stanford and the University of Michigan. Burcu holds a PhD in number theory.

Kathy Baxter is architect for ethical AI practice at Salesforce, where she develops research-informed best practices to educate employees, customers, and the industry on the development of ethical AI. She partners and collaborates with external AI and ethics experts to continuously evolve policies, practices, and products—working to create a more fair, justice, and equitable society. You can read about her research on the Salesforce UX Medium channel. Kathy has 20 years of experience in the tech industry, at companies including Google, eBay, and Oracle. She holds an MS in engineering psychology and a BS in applied psychology from the Georgia Institute of Technology. The second edition of her book, Understanding Your Users, was published in May 2015.

Maxime Beauchemin is a senior software engineer at Lyft, where he develops open source products that reduce friction and help generate insights from data. He’s the creator and a lead maintainer of data pipeline workflow engine Apache Airflow (incubating) and data visualization platform Apache Superset (incubating). A recognized thought leader in the data engineering field, Maxime previously worked on the analytics and experimentation products team at Airbnb; at Facebook, where he focused on computation frameworks powering engagement and growth analytics; at Yahoo, where he did clickstream analytics; and at Ubisoft, where he was a data warehouse architect.

John Bennett leads the data engineering efforts within Netflix’s cloud infrastructure analytics team with a focus on security. For the past three years, he has built large-scale data processing systems that provide anomaly detection, network visibility, and dependency insights. John has been writing code for almost 20 years. His previous roles include stints at Blizzard and IGN. John is currently developing a template-driven platform that enables engineers to rapidly build streaming and batch ETL pipelines for detection purposes.

Till Bergmann is a senior data scientist at Salesforce Einstein, building platforms to make it easier to integrate machine learning into Salesforce products, with a focus on automating many of the laborious steps in the machine learning pipeline. He holds a PhD in cognitive science from the University of California, Merced, where he studied the collaboration patterns of academics using NLP techniques.

Josh Bersin is an analyst, author, educator, and thought leader focusing on the global talent market and the challenges and trends impacting business workforces around the world. He studies the world of work, HR and leadership practices, and the broad talent technology market. He is often cited as one of the leading HR and workplace industry analysts in the world. He founded Bersin & Associates in 2001 to provide research and advisory services focused on corporate learning. Over the next 10 years, he expanded the company’s coverage to encompass HR, talent management, talent acquisition, and leadership and became a recognized expert in the talent market. He sold the company to Deloitte in 2012, when it became known as Bersin by Deloitte. He continues to serve as a senior advisor to Deloitte, advising large organizations and contributing to major research initiatives. He also sits on the board of UC Berkeley Executive Education. Previously, Josh spent 25 years in product development, product management, marketing, and sales of e-learning and other enterprise technologies.

Josh is frequently featured in talent and business publications such as Forbes, Harvard Business Review, HR Executive, FastCompany, the Wall Street Journal, and CLO Magazine. He is a regular keynote speaker at industry events and a popular blogger with more than 700,000 followers on LinkedIn. He is the author of two books—The Blended Learning Handbook and The Training Measurement Book—along with dozens of studies on corporate HR, learning, and talent technologies. His third book is currently under contract with Harvard Business Publishing. Josh holds a BS in engineering from Cornell University, an MS in engineering from Stanford University, and an MBA from the Haas School of Business at the University of California, Berkeley.

Maneesha Bhalla is director of advanced analytics at Office Depot. A thought leader with 16+ years of experience in data analytics and data science specifically in customer analytics, Maneesha is passionate about data-driven approaches to turn data into insights and has a proven ability to build and lead highly efficient teams to enable the organization’s strategic priorities. Maneesha holds a certificate from the Executive Management Program in Global Business Management at IIM Calcutta and a bachelor’s degree in chemical engineering from Pune University.

Ron Bodkin is a technical director on the applied artificial intelligence team at Google, where he provides leadership for AI success for customers in Google’s Cloud CTO office. Ron engages deeply with Global F500 enterprises to unlock strategic value with AI, acts as executive sponsor with Google product and engineering to deliver value from AI solutions, and leads strategic initiatives working with customers and partners. Previously, Ron was the founding CEO of Think Big Analytics, a company that provides end-to-end support for enterprise big data, including data science, data engineering, advisory, and managed services and frameworks such as Kylo for enterprise data lakes. When Think Big was acquired by Teradata, Ron led global growth, the development of the Kylo open source data lake framework, and the company’s expansion to architecture consulting; he also created Teradata’s artificial intelligence incubator.

Dhruba Borthakur is cofounder and CTO at Rockset, a company building software to enable data-powered applications. Dhruba was the founding engineer of the open source RocksDB database at Facebook and one of the founding engineers of the Hadoop File System at Yahoo. Dhruba was also an early contributor to the open source Apache HBase project. Previously, he was a senior engineer at Veritas Software, where he was responsible for the development of VxFS and Veritas SanPointDirect storage system; was the cofounder of Oreceipt.com, an ecommerce startup based in Sunnyvale; and was a senior engineer at IBM-Transarc Labs, where he contributed to the development of Andrew File System (AFS), a part of IBM’s ecommerce initiative, WebSphere. Dhruba holds an MS in computer science from the University of Wisconsin-Madison and a BS in computer science BITS, Pilani, India. He has 25 issued patents.

Katherine Boyle is a principal at General Catalyst, a bicoastal venture capital firm with $5B under management. She focuses on early-stage investments in frontier technology and highly regulated industries, including aerospace, defense, computational biology, robotics, and autonomous mobility. Before becoming an investor, she was a staff reporter at the Washington Post, where her features and investigations appeared in every section of the paper (except Sports). Katherine holds an MBA from the Stanford Graduate School of Business, where she was research and teaching assistant to Condoleezza Rice and Amy Zegart for their course and newly released book Political Risk: How Businesses and Organizations Can Anticipate Global Insecurity. She’s a graduate of Georgetown University and holds a master’s degree in public advocacy from National University of Ireland, Galway, where she was George J. Mitchell Scholar.

Catherine Bracy is a civic technologist and community organizer whose work focuses on the intersection of technology and political and economic inequality. She is the cofounder and executive director of the TechEquity Collaborative, an organization in Oakland, CA, that seeks to build a tech-driven economy in the Bay Area that works for everyone. Previously, she was senior director of partnerships and ecosystem at Code for America, where she grew the Brigade program into a network of over 50,000 civic tech volunteers in 80+ cities across the US. She also founded Code for All, the global network of Code-for organizations with partners on six continents. Catherine built Code for America’s civic engagement focus area, creating a framework and best practices for local governments to increase public participation which has been adopted in cities across the US. During the 2012 election cycle, she was director of Obama for America’s Technology Field Office in San Francisco, the first of its kind in American political history. She was responsible for organizing technologists to volunteer their skills for the campaign’s technology and digital efforts. Prior to joining the Obama campaign, she ran the Knight Foundation’s 2011 News Challenge and was the administrative director at Harvard’s Berkman Center for Internet & Society. She is on the board of directors at the Data & Society Research Institute and the Public Laboratory.

Eric T. Bradlow is chairperson of the Marketing Department, the K.P. Chao Professor, a professor of marketing, statistics, economics, and education, and faculty director of the Wharton Customer Analytics Initiative at the Wharton School of the University of Pennsylvania. His academic research interests include Bayesian modeling, statistical computing, and developing new methodology for unique data structures with application to business problems, education, and psychometrics and health outcomes. Previously, Eric was editor in chief of Marketing Science, the premier academic journal in marketing. He was recently named one of eight inaugural University of Pennsylvania Fellows, a fellow of the American Statistical Association, a fellow of the American Education Research Association, a fellow of the Wharton Risk Center, and a senior fellow of the Leonard Davis Institute for Health Economics. He is a past chair of the American Statistical Association Section on Statistics in Marketing and is a statistical fellow of Bell Labs. He was previously named DuPont Corporation’s best young researcher and has won research awards in marketing, statistics, psychology, education, and medicine. Eric holds a BS in economics from the Wharton School and an AM in mathematical statistics and a PhD in mathematical statistics from Harvard University. His personal interests include his wife, Laura, and his sons, Ethan, Zach, and Ben. He also loves sports and movies.

Claudiu Branzan is an analytics senior manager in the Applied Intelligence Group at Accenture, based in Seattle, where he leverages his more than 10 years of expertise in data science, machine learning, and AI to promote the use and benefits of these technologies to build smarter solutions to complex problems. Previously, Claudiu held highly technical client-facing leadership roles in companies using big data and advanced analytics to offer solutions for clients in healthcare, high-tech, telecom, and payments verticals.

Avner Braverman is cofounder and CEO of Binaris, building an applications optimized serverless platform. Avner’s full stack ranges from hardware architecture, through kernel design and up to JavaScript applications.
He’s been working with distributed operating systems since his school days. Previously, he cofounded XIV, a distributed storage company, Parallel Machines, and a high-performance analytics company.

Mark Brine is the director of finance of Cloudera.

Kurt Brown leads the data platform team at Netflix, which architects and manages the technical infrastructure underpinning the company’s analytics, including various big data technologies like Hadoop, Spark, and Presto, machine learning infrastructure for Netflix data scientists, and traditional BI tools including Tableau.

Stuart Buck is the vice president of research at Arnold Ventures, one of the leading funders of research to inform public policy. He has given advice to DARPA, IARPA (the CIA’s research arm), and the White House Social and Behavioral Sciences Team on rigorous research processes. He has sponsored major efforts showing that even the best scientific research is often irreproducible; this work has been featured in Wired, the Economist, the New York Times, and the Atlantic. He has also published in top journals (such as Science and BMJ) on how to make research more accurate. He holds a PhD in education policy from the University of Arkansas, where he studied econometrics, statistics, and program evaluation; a JD with honors from Harvard Law School, where he was an editor of the Harvard Law Review; and bachelor’s and master’s degrees in music performance from the University of Georgia.

Saumitra Buragohain is a vice president of product management for Hortonworks Data Platform (HDP). During his tenure, Saumitra led the launch of HDP 3.0.0 and first DataPlane application, Data Lifecycle Manager, from concept to business case to release. Saumitra holds an MBA from Santa Clara University and an MSEE from the University of Southern California.

Andrew is Managing Partner at bnh.ai, a boutique law firm focused on AI and analytics, and Chief Legal Officer at Immuta. He is also a Visiting Fellow at Yale Law School’s Information Society Project. Previously, Andrew served as Special Advisor for Policy to the head of the Federal Bureau of Investigation’s Cyber Division, where he served as lead author on the FBI’s after action report for the 2014 attack on Sony.

A leading authority on the intersection between law and technology, Andrew has published articles in The New York Times, The Financial Times, and Harvard Business Review, where he is a regular contributor.

Andrew is a term-member of the Council on Foreign Relations, a member of the Washington, D.C. and Virginia State Bars, and a certified cyber incident response handler. He holds a JD from Yale Law School and a BA with first-class honors from McGill University.

Chris Bush is the head of digital analytics and data science at Levi Strauss & Co., where he established and continues to grow the analytics and data science practice. His responsibilities include increasing the data centricity, providing analytical insights, and powering personalization and optimization efforts. Previously, Chris founded the product analytics team at Walmart Labs, where he was responsible for providing product analytics and overseeing the implementation of clickstream analytics on Walmart-owned websites and apps and drove hypothesis-led inquiries to investigate business critical issues and prioritize opportunities. In a prior career, he practiced law at Latham & Watkins LLP, where he developed bespoke equity derivatives, quantitative structured products, and novel equity products.

Igor Canadi is a software engineer at Rockset, where he is developing its data indexing and distributed SQL query engine. Previously, Igor was an engineer at Facebook, working on the database engineering and product infrastructure teams, where he contributed to RocksDB, developed MongoRocks and MongoDB with RocksDB storage engine, drove RocksDB open source initiatives, worked on core GraphQL infrastructure for Facebook’s Android application, and owned GraphQL developer tooling for hundreds of developers. Igor holds a master’s degree in computer science from the University of Wisconsin-Madison and a bachelor’s degree from the University of Zagreb. In his free time, he likes sailing and snowboarding.

Sarah Catanzaro is a principal at Amplify Partners, where she focuses on investing in high-potential startups that leverage machine intelligence and high-performance computing to solve real-world problems. Previously, Sarah co-led investments in Kinetica, Platform9, and Fluxx at Canvas Ventures. Sarah has several years of experience in developing data acquisition strategies and leading machine and deep learning-enabled product development at organizations of various sizes: As head of data at Mattermark, she led a team to collect and organize information on over one million private companies; as a consultant at Palantir and as an analyst at Cyveillance, she implemented analytics solutions for municipal and federal agencies; and as a program manager at the Center for Advanced Defense Studies, she directed projects on adversary behavioral modeling and Somali pirate network analysis. Sarah holds a BA in international security studies from Stanford University.

Principal Developer Advocate for Streaming Services with AWS.

Raghu Chakravarthi is the senior vice president at Actian, where he’s responsible for products, R&D, and support services and leads the teams that make sure that business-critical systems can transact and integrate at their very best through the deployment of highly scalable data management technology, underpinned by a relentless and trusted service commitment, both on-premises and in the cloud. He’s passionate about data and uncovering real insights using analytics and is a seasoned product development executive with experience in commercial enterprise software at both large and in startup companies. Previously, Raghu was the general manager and vice president of engineering at Teradata for the Vantage Platform and served in executive roles at Oracle and Hyperion. He’s active in the Silicon Valley tech corridor with speaking engagements, networking events, and hosting meetups.

James Cham is a partner at Bloomberg Beta, a seed-stage VC firm investing in startups that make work better. Previously, he was a VC at Bessemer Venture Partners and Trinity Ventures. He started his career as a software developer.

Jian Chang is a senior algorithm expert at the Alibaba Group, where he is working on cutting-edge applications of AI at the intersection of high-performance databases and the IoT, focusing on unleashing the value of spatiotemporal data. A data science expert and software system architect with expertise in machine learning and big data systems and deep domain knowledge on various vertical use cases (finance, telco, healthcare, etc.), Jian has led innovation projects and R&D activities to promote data science best practices within large organizations. He’s a frequent speaker at technology conferences, such as the O’Reilly Strata and AI Conferences, NVIDIA’s GPU Technology Conference, Hadoop Summit, DataWorks Summit, Amazon re:Invent, Global Big Data Conference, Global AI Conference, World IoT Expo, and Intel Partner Summit, and has published and presented research papers and posters at many top-tier conferences and journals, including ACM Computing Surveys, ACSAC, CEAS, EuroSec, FGCS, HiCoNS, HSCC, IEEE Systems Journal, MASHUPS, PST, SSS, TRUST, and WiVeC. He’s also served as a reviewer for many highly reputable international journals and conferences. Jian holds a PhD from the Department of Computer and Information Science (CIS) at University of Pennsylvania, under Insup Lee.

Haifeng Chen is a senior software architect at Intel’s Asia Pacific R&D Center. He has more than 12 years’ experience in software design and development, big data, and security, with a particular interest in image processing. Haifeng is the author of image browsing, editing, and processing software ColorStorm.

Jeff Chen is the chief innovation officer at the US Bureau of Economic Analysis, where he’s responsible for integrating advancements in data science and machine learning to advance the bureau’s capabilities. A statistician and data scientist, Jeff has extensive experience in launching and leading data science initiatives in over 40 domains, working with diverse stakeholders such as firefighters, climatologists, and technologists, among others to introduce data science and new technologies to advance their missions. Previously, he was the chief scientist at the US Department of Commerce; a White House Presidential Innovation Fellow with NASA and the White House Office of Science and Technology Policy, focused on data science for the environment; the first director of analytics at the NYC Fire Department, where he engineered pioneering algorithms for fire prediction; and on of the first data scientists at the NYC Mayor’s Office under then-Mayor Mike Bloomberg. Jeff started his career as an econometrician at an international engineering consultancy, where he developed forecasting and prediction models supporting for large-scale infrastructure investment projects. In the evenings, he’s an adjunct professor of data science at Georgetown University. He holds a bachelor’s degree in economics from Tufts University and a master’s degree in applied statistics from Columbia University.

Roger Chen is cofounder and CEO of Computable and program chair for the O’Reilly Artificial Intelligence Conference. Previously, he was a principal at O’Reilly AlphaTech Ventures (OATV), where he invested in and worked with early-stage startups primarily in the realm of data, machine learning, and robotics. Roger has a deep and hands-on history with technology. Before startups and venture capital, he was an engineer at Oracle, EMC, and Vicor. He also developed novel nanoscale and quantum optics technology as a PhD researcher at UC Berkeley. Roger holds a BS from Boston University and a PhD from UC Berkeley, both in electrical engineering.

Sanjian Chen is a Senior Algorithm Expert at the Alibaba Group. He has deep knowledge of large-scale machine learning algorithms. Over his career, he’s partnered with and advised leaders at several Fortune 500 companies on making data-driven strategic decisions and provided software-based data analytics consulting service to seven global firms across multiple industries, including financial services, automotive, telecommunications, and retail.

Shouwei Chen is an ECE PhD student at Rutgers University, advised by Ivan Rodero. Shouwei’s research focuses on the codesign of a memory-centric computing framework with an in-memory distributed filesystem.

Tim Chen is a software engineer at Cloudera leading cloud initiatives for the company’s enterprise machine learning platform. Previously, he was cofounder and CEO and cofounder of Hyperpilot, a startup focused on applying machine learning to improve performance and cost efficiency of container clusters and big data workloads, led containerization development and design at Mesosphere, and worked at VMware and Microsoft. He’s an Apache PMC member and committer on Apache Drill and Apache Mesos and helped initiate the Spark-on-Kubernetes project and led development of Mesos support for Spark.

Chakri Cherukuri is a senior researcher in the Quantitative Financial Research Group at Bloomberg LP in NYC. His research interests include quantitative portfolio management, algorithmic trading strategies, and applied machine learning. He has extensive experience in scientific computing and software development. Previously, he built analytical tools for the trading desks at Goldman Sachs and Lehman Brothers. He holds an undergraduate degree in mechanical engineering from the Indian Institute of Technology (IIT) Madras, India, and an MS in computational finance from Carnegie Mellon University.

Alan Chin is a contributor working on Jupyter Enterprise Gateway and an open source advocate at IBM. His previous roles include build and release engineer and test engineer in DB2 on z/OS. In a previous life, he served as a crew chief with the 15th in Hurlburt Field and 16th ESOS in Afghanistan. Alan holds a BS in computer science from San Jose State University. He resides in San Francisco with his wife and three furry children (two cats and a dog).

Divya Choudhary is a researcher and graduate student in data science at USC. A computer science engineer turned decision scientist turned data scientist, Divya is known for her business understanding, approach to problem solving, machine learning, NLP, and driving data science problems to the final execution. She has four years’ experience unveiling the wonders of data using data science. Previously, she was a data scientist at GOJEK and worked closely with the boards of directors of three startups in India and Indonesia. She’s a yoga lover, painter, poetess, and avid trekker and wanderer who’s best at talking to people and learning about them.

Rumman Chowdhury is a senior manager and AI lead at Accenture, where she works on cutting-edge applications of artificial intelligence and leads the company’s responsible and ethical AI initiatives. She also serves on the board of directors for three AI startups. Rumman’s passion lies at the intersection of artificial intelligence and humanity. She comes to data science from a quantitative social science background. She has been interviewed by Software Engineering Daily, the PHDivas podcast, German Public Television, and fashion line MM LaFleur. In 2017, she gave talks at the Global Artificial Intelligence Conference, IIA Symposium, ODSC Masterclass, and the Digital Humanities and Digital Journalism conference, among others. Rumman holds two undergraduate degrees from MIT and a master’s degree in quantitative methods of the social sciences from Columbia University. She is near completion of her PhD from the University of California, San Diego.

Eric Colson is chief algorithms officer at Stitch Fix, where he leads a team of 100+ data scientists and is responsible for the multitude of algorithms that are pervasive to nearly every function of the company, from merchandise, inventory, and marketing to forecasting and demand, operations, and the styling recommender system. He’s also an advisor to several big data startups. Previously, Eric was vice president of data science and engineering at Netflix. He holds a BA in economics from SFSU, an MS in information systems from GGU, and an MS in management science and engineering from Stanford.

Ian Cook is a data scientist at Cloudera and the author of several R packages, including implyr. Previously, he was a data scientist at TIBCO and a statistical software developer at AMD. Ian is a cofounder of Research Triangle Analysts, the largest data science meetup group in the Raleigh, North Carolina, area, where he lives with his wife and two young children. He holds an MS in statistics from Lehigh University and a BS in applied mathematics from Stony Brook University.

Will Crichton is a PhD student in computer science at Stanford, advised by Pat Hanrahan. He creates systems that merge research in parallel computing and programming language design to solve impactful problems. Will’s current focus is on tools to enable large-scale visual data analysis, or processing massive collections of images and videos, including published work at SIGGRAPH.

Alistair Croll is an entrepreneur with a background in web performance, analytics, cloud computing, and business strategy. In 2001, he cofounded Coradiant (acquired by BMC in 2011) and has since helped launch Rednod, CloudOps, Bitcurrent, Year One Labs, and several other early-stage companies. He works with startups on business acceleration and advises a number of larger companies on innovation and technology. A sought-after public speaker on data-driven innovation and the impact of technology on society, Alistair has founded and run a variety of conferences, including Cloud Connect, Bitnorth, and the International Startup Festival, and is the chair of O’Reilly’s Strata Data Conference. He has written several books on technology and business, including the best-selling Lean Analytics. Alistair tries to mitigate his chronic ADD by writing about far too many things at Solve For Interesting.

Anne Cruz is the manager of merchandising and supply chain technology at Walgreens. She’s currently working on Walgreens Retail’s multiyear transformation journey, in which data strategy is pivotal to how business strategy is synthesized with technology. Anne is the IT partner for supply chain analytics that enable the business with capabilities to accelerate business value through changing operating models, simplifying and modernizing architectures, and collaborating with business units and other IT functions to redesign and optimize business processes.

Dillon Cullinan is a data engineering cybersecurity specialist at Accenture Cyber Labs, located in the Washington, DC, area. Dillon focuses on building big data solutions for the cybersecurity realm to enable large-scale analytics and visualizations.

Nick Curcuru is vice president of enterprise information management at Mastercard, where he’s responsible for leading a team that works with organizations to generate revenue through smart data, architect next-generation technology platforms, and protect data assets from cyberattacks by leveraging Mastercard’s information technology and information security resources and creating peer-to-peer collaboration with their clients. Nick brings over 20 years of global experience successfully delivering large-scale advanced analytics initiatives for such companies as the Walt Disney Company, Capital One, Home Depot, Burlington Northern Railroad, Merrill Lynch, Nordea Bank, and GE. He frequently speaks on big data trends and data security strategy at conferences and symposiums, has published several articles on security, revenue management, and data security, and has contributed to several books on the topic of data and analytics.

Principal Solutions Architect at Weaveworks, previously a Principal Engineer at MapR.

Doug Cutting is the chief architect at Cloudera and the founder of numerous successful open source projects, including Lucene, Nutch, Avro, and Hadoop. Doug joined Cloudera from Yahoo, where he was a key member of the team that built and deployed a production Hadoop storage-and-analysis cluster for mission-critical business analytics. Doug holds a bachelor’s degree from Stanford University and sits on the board of the Apache Software Foundation.

Sabrina Dahlgren is a director in charge of strategic analysis at Kaiser Permanente. Her expertise ranges from statistics and economics to project management and computer science. Sabrina has 20 years’ total work experience in leadership and analytical roles such as vice president of marketing and product development and CRM manager and customer segmentation in technology companies including Vodafone, among others. Sabrina has twice won the Innovation Award at Kaiser, most recently in the category of broadly applicable technology for big data analytics.

Jason Dai is a senior principal engineer and chief architect for big data technologies at Intel, where he leads the development of advanced big data analytics, including distributed machine learning and deep learning. Jason is an internationally recognized expert on big data, the cloud, and distributed machine learning; he’s the cochair of the Strata Data Conference in Beijing, a committer and PMC member of the Apache Spark project, and the creator of BigDL, a distributed deep learning framework on Apache Spark.

Stephen Dantu is the head of big data capabilities at Marsh, where he leads the strategy, roadmap, and delivery of Marsh’s big data ecosystem to power next-gen data, analytics, and self-service capabilities across the company. He’s also an analytics evangelist, empowering the organization with a variety of self-service utilities and promoting the cause of democratizing data. Stephen is a seasoned, hands-on data and analytics leader with passion and expertise in unleashing the power of data through robust data platforms and cutting-edge analytics. Previously, he led internal analytics at Mastercard, where he was responsible for driving the strategy and execution of the company’s internal analytics BI platforms and providing consultative analytics support on strategic initiatives. He conceived and led the creation of the Centralized Analytics Hub to democratize big data by delivering fast, curated analytics coupled with best-in-class visualization.

Michelle Davenport is one of the most sought-after nutrition experts in food and tech. Currently Michelle consults startups and larger companies on data science in nutrition data analysis and precision-based methods to food and health product research and development. She also serves as a clinical and scientific advisor to startups, including Ritual, a direct-to-consumer supplement company for women. Previously, she was the cofounder and president of Raised Real, where she created a venture-funded, tech-driven, subscription food program for children that targets infant nutritional milestones. As the fastest growing kids’ food brand in the US, Raised Real currently delivers to thousands of families nationwide. Before that, she was the director of nutrition for Zesty (acquired by Square), where she developed the food and nutrition API and a proprietary nutrient analysis program. Michelle and her work have been featured in Fast Company, Forbes, Time, and the Wall Street Journal, among others. She lives in Menlo Park, CA, with her husband, Josh, and daughter, Sophie. Michelle holds a PhD in nutrition from New York University; she did her clinical training as a registered dietitian at the University of California, San Francisco.

Julien Delange is a staff software engineer at Twitter working on infrastructure services. Previously, he was a senior software engineer at Amazon Web Services, a senior member of the technical staff at Carnegie Mellon University, and a software engineer at the European Space Agency. Julien holds a PhD in computer science from Télécom ParisTec and a master’s degree in computer science from Université Pierre-et-Marie-Curie.

Sourav Dey is CTO at Manifold, an artificial intelligence engineering services firm with offices in Boston and Silicon Valley. Sourav leads the engineering team focusing on work across client projects, developing platform technologies to make Manifold ML engineers more efficient, and communicating to business stakeholders. Prior to Manifold, Sourav led teams building data products across the technology stack, from smart thermostats and security cams at Google-Nest to wireless communication at Qualcomm. Sourav’s career has always been at the intersection of math and computer science — a PhD from MIT in signal processing and bachelors degrees in Math and CS from MIT.

Rohan Dhupelia leads the analytics platform team at Atlassian, which focuses on further democratizing data in the company and providing a world-class, highly innovative data platform. Rohan has spent the last 10+ years of his career in the data space across a variety of industries, including FMCGs, property, and technology, doing everything from BI report development to data warehousing and data engineering.

Renee DiResta is Director of Research at cybersecurity company New Knowledge and a Mozilla Fellow in Media, Misinformation, and Trust. She investigates the spread of disinformation and malign narratives across social networks, and has advised the Congress, the State Department, and senior executives on how to understand and respond to influence operations.

Louis DiValentin is a security data scientist at Accenture Cyber Labs, located in the Washington, DC, area. His research focuses on security analytics modeling, graph analytics, and big data.

Thomas Dobbs is a data science product manager at KIXEYE, where he is responsible for maintaining and building machine learning models from ideation to full implementation. Thomas also wrote the underlying algorithm for KIXEYE’s offer recommendation engine. His experience spans marketing, user acquisition, finance, and product, and he has spent seven years in the gaming industry. He is an MBA candidate at UC Berkeley’s Haas School of Business.

Harish Doddi is cofunder and CEO of Datatron. Previously, he held roles at Oracle; Twitter, where he worked on open source technologies, including Apache Cassandra and Apache Hadoop, and built Blobstore, Twitter’s photo storage platform; Snap, where he worked on the backend for Snapchat Stories; and Lyft, where he worked on the surge pricing model. Harish holds a master’s degree in computer science from Stanford, where he focused on systems and databases, and an undergraduate degree in computer science from the International Institute of Information Technology in Hyderabad.

Xiaojing Dong is head of marketing science and a staff data scientist on the data science team at LinkedIn. She’s also an associate professor of marketing and business analytics at Santa Clara University, where she led the effort in designing and starting a popular Master of Science program in business analytics and served as the founding director. She helps translate business and marketing problems into data questions and apply analytical techniques into solving such problems to assist business decisions.

Mark Donsky is a director of product management at Okera, a software provider that provides discovery, access control, and governance at scale for today’s modern heterogenous data environments, where he leads product management. Previously, Mark led data management and governance solutions at Cloudera, and he’s held product management roles at companies such as Wily Technology, where he managed the flagship application performance management solution, and Silver Spring Networks, where he managed big data analytics solutions that reduced greenhouse gas emissions by millions of dollars annually. He holds a BS with honors in computer science from the Western University, Ontario, Canada.

Jed Dougherty is a data scientist at Dataiku, where he leads the data scientist team in North America. He specializes in helping large companies in fields including finance, manufacturing, and medicine spin up and organize data science teams and has helped clients build successful projects in data security, real-time recommendation, predictive maintenance, and other “hot topics.” Previously, he worked at a camel ride, so he’s spent quite a bit of time appreciating the normal versus bimodal distribution of dromedaries and Bactrians. He holds a master’s degree from the QMSS program at Columbia University.

Justin Driemeyer is an ML staff engineer at 8×8. Previously, he spent three years at an ML B2B advertising startup (acquired by 8×8) and seven years at Zynga, as it went from a 10-person startup to a 2,000-person public company. He holds a BS in computer engineering from U of I and an MS in CS from Stanford, where he worked on the STAIR project.

Alain Dufaux is head of operations and development for the Metamedia Center at École Polytechnique Fédérale de Lausanne (EPFL), which is responsible for digitization and preservation of the Montreux Jazz Festival archive. Previously, he worked at a company developing ultra-low-power processors and real-time algorithms for hearing aid devices and worked in a research lab at EPFL managing projects and coaching students in the development of image and video processing algorithms applied to vision systems. He holds a PhD from the University of Neuchâtel, Switzerland, where his thesis was dedicated to automatic sound recognition.

Ted Dunning is the chief technology officer at MapR, an HPE company. He’s also a board member for the Apache Software Foundation, a PMC member, and committer on a number of projects. Ted has years of experience with machine learning and other big data solutions across a range of sectors. He’s contributed to clustering, classification, and matrix decomposition algorithms in Mahout and to the new Mahout Math library and designed the t-digest algorithm used in several open source projects and by a variety of companies. Previously, Ted was chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems and built fraud-detection systems for ID Analytics (LifeLock). Ted has coauthored a number of books on big data topics, including several published by O’Reilly related to machine learning, and has 24 issued patents to date plus a dozen pending. He holds a PhD in computing science from the University of Sheffield. When he’s not doing data science, he plays guitar and mandolin. He also bought the beer at the first Hadoop user group meeting.

Taposh Roy leads the innovation team within the Decision Support Group at Kaiser Permanente. His work focuses on journey analytics, deep learning, data science architecture, and strategy. A consumer-focused machine learning and data science geek, Taposh has a unique combination of product, technology and strategy consulting, data science, and startup experience. Previously, he was head of AD products at Inpowered and Netshelter (acquired by Ziff Davis); senior associate consultant in MIT-based consulting company Sapient; and cofounder of biotech company Bio-Integrated Solutions, where he developed DNA sequencers and liquid handling devices for proteomics.

Bysshe Easton is the director of analytics at KIXEYE, where he brings his experience using a combination of data analysis, economics, intuition, and game design sense to solve monetization and content delivery problems in games. He also manages the insights and implementations of the machine learning offer system for War Commander: Rogue Assault.

Jana Eggers is CEO of Nara Logics, a neuroscience-inspired artificial intelligence company providing a platform for recommendations and decision support. A math and computer nerd who took the business path, Jana has had a career that’s taken her from a three-person business to fifty-thousand-plus-person enterprises. She opened the European logistics software offices as part of American Airlines, dove into the internet in ’96 at Lycos, founded Intuit’s corporate Innovation Lab, helped define mass customization at Spreadshirt, and researched conducting polymers at Los Alamos National Laboratory. Her passions are working with teams to define and deliver products customers love, algorithms and their intelligence, and inspiring teams to do more than they thought possible.

Susan Etlinger is an industry analyst at Altimeter. Her research focuses on the impact of artificial intelligence, data, and advanced technologies on business and culture and is used in university curricula around the world. Susan’s TED Talk, “What do we do with all this big data?,” has been translated into 25 languages and has been viewed more than 1.2 million times. She’s a sought-after keynote speaker and has been quoted in such media outlets as the Wall Street Journal, the BBC, and the New York Times.

Adam Famularo is CEO of erwin, Inc., maker of the world’s number-one data modeling software as well as other data management solutions that help organizations derive maximum results from their data initiatives and promote strong data governance. Previously Adam oversaw Verizon’s enterprise distribution channels—partners, value-added resellers, and systems integrators—across the world and served as a senior vice president and general manager for CA Technologies’s cloud computing business and storage and data management business units.

Wenchen Fan is a software engineer at Databricks, working on Spark Core and Spark SQL, as well as a Spark committer and a Spark PMC member. He mainly focuses on the Apache Spark open source community, leading the discussion and reviews of many features and fixes in Spark.

Tao Feng is a software engineer on the data platform team at Lyft. Tao is a committer and PMC member on Apache Airflow. Previously, Tao worked on data infrastructure, tooling, and performance at LinkedIn and Oracle.

Toby Ferguson is a sales engineer at Cloudera, where he helps partners succeed with the Cloudera platform.

Rustem Feyzkhanov is a machine learning engineer at Instrumental, where he creates analytical models for the manufacturing industry. Rustem is passionate about serverless infrastructure (and AI deployments on it) and is the author of the course and book Serverless Deep Learning with TensorFlow and AWS Lambda.

Erin Flynn is the chief people officer at Optimizely, where she oversees recruiting, people operations, real estate, and workplace operations. Erin’s more than 20 years of experience includes a decade leading recruiting, talent development, and employee success (global HR) at Salesforce as well as stints with PeopleSoft and Idealab. When she’s not making Optimizely one of the best places to work, she also sits on the board of the Horizons Foundation.

Ash Fontana is managing director of Zetta Venture Partners—the first venture capital fund focused on intelligent systems, which he launched with Mark Gorenberg. The firm has $185M under management and has invested in 21 companies. Ash is a board member of and lead investor in companies such as Kaggle, Invenia, Clearbit, Tractable, and Focal Systems. Previously, Ash started the money side of AngelList, the most successful startup investing platform in the world; he launched online investing, managing $130M over more than 250 funds, creating the first startup index fund, and curating investment opportunities across 500,000 companies. He also ran special projects like AngelList’s expansion into Europe and the UK and simultaneously led syndicates and angel investments in Canva, Mixmax, and others. Ash cofounded Topguest, a Founders Fund-backed company that built customer analytics technology for companies like IHG, United, and Caesars Entertainment. Topguest sold in an eight-figure transaction 18 months after the company was founded.

Jonathan Foster is the principal content experiences manager at Microsoft, where he leads the Windows and content intelligence writing team. Their work includes UX writing, designing personality and voice within products and experiences, and authoring and designing conversational interactions for products and experiences. He built the writing team for Microsoft’s digital assistant Cortana for the US and international markets, which focused on the development of Cortana’s personality while crafting fun, challenging dialogue. They’re now expanding upon this knowledge to create a personality catalogue for Microsoft’s Bot framework and train a deep neural net conversational model to support those personalities. Jonathan started out in film and television writing screenplays and working in development. He was eventually drawn away from Hollywood by the true innovative spirit of the tech industry, starting with an interactive storytelling project that was honored by the Sundance Film Festival.

Don Fox is a Boston-based data scientist in residence at the Data Incubator. Previously, Don developed numerical models for a geothermal energy startup. Born and raised in South Texas, Don holds a PhD in chemical engineering, where he researched renewable energy systems and developed computational tools to analyze the performance of these systems.

Jonathan Francis is vice president of marketing analytics and optimization at Starbucks.

Bill Franks is chief analytics officer at the International Institute for Analytics (IIA). His work has spanned clients in a variety of industries for companies ranging in size from Fortune 100 companies to small nonprofit organizations. Previously, he was chief analytics officer at Teradata. Bill is the author of Taming the Big Data Tidal Wave and The Analytics Revolution. You can learn more on his website.

Brandon Freeman is a Mid-Atlantic region strategic system engineer at Cloudera, specializing in infrastructure, the cloud, and Hadoop. Previously, Brandon was an infrastructure architect at Explorys, working in operations, architecture, and performance optimization for the Cloudera Hadoop environments, where he was responsible for designing, building, and managing many large Hadoop clusters.

Cynthia Freeman is a research engineer at Verint Intelligent Self-Service, a developer of conversational AI systems. She holds an MS in applied mathematics from the University of Washington and a BS in mathematics from Gonzaga University and is currently pursuing her PhD in computer science at the University of New Mexico, where she works on time series analysis and developing new anomaly detection methods.

Matt Fuller is cofounder at Starburst, the Presto company. Previously, Matt has held engineering roles in the data warehousing and analytics space for the past 10 years, including director of engineering at Teradata, where he led engineering teams working on Presto and was part of the team that led the initiative to bring open source, in particular Presto, to Teradata’s products; architected and led development efforts for the next-generation distributed SQL engine at Hadapt (acquired by Teradata in 2014); and was an early engineer at Vertica (acquired by HP), where he worked on the query optimizer.

Mei Lin Fung is a technology pioneer working to ensure that technology works for humanity as the next 3.9 billion people come online. In 1989, she was part of the two-person skunkworks team that developed OASIS, the first customer relationship management (CRM) system. She later served as sociotechnical lead for the US Department of Defense’s Federal Health Futures initiative. In 2015, she joined “father of the internet” Vint Cerf to cofound the People-Centered Internet, which maintains a global network of “positive change agents” committed to ensuring that technology is developed with a people-centered focus—increasing access while ensuring equality, protecting the vulnerable, and prioritizing human well-being. She serves on the World Economic Forum Steering committee for Internet for All. She chairs the Industry Connections Social Impact Measurement Pre-standards working group for the Institute for Electrical and Electronic Engineers (IEEE), and is liaison to the Standards Association for the IEEE Humanitarian Activities Committee. She is founder and unit coordinator of the California Health Medical Reserve Corps.

Krishna Gade is the founder and CEO of Fiddler Labs, an enterprise startup building an explainable AI engine to address problems regarding bias, fairness, and transparency in AI. An entrepreneur and engineering leader with a strong technical experience of creating scalable platforms and delightful consumer products, Krishna previously held senior engineering leadership roles at Facebook, Pinterest, Twitter, and Microsoft.

Li Gao is the tech lead for the Cloud Native Spark Compute Initiative at Lyft. Previously, Li held technical leadership positions focusing on cloud native and hybrid cloud data platforms at scale at Salesforce, Fitbit, Marin Software, and a few startups. Besides Spark, Li has scaled and productionized open source projects including Presto, Apache HBase, Apache Phoenix, Apache Kafka, Apache Airflow, and Apache Hive.

Sarah Gates is the product marketer for the SAS Platform. Previously, she spent five years as an analytics advisor at SAS, where she helped government customers on the West Coast leverage their data to better serve their citizens. Prior to joining SAS, she was the vice president of research for the International Institute for Analytics, where she advised clients worldwide in the healthcare, retail, banking, and manufacturing industries on analytic applications and analytic program maturity. She also has 20 years of experience in the government sector in a wide variety of data scientist, policy, and leadership roles. Sarah holds a degree in mathematics and an MBA from Willamette University. She’s passionate about cycling and her two daughters, one of whom she has successfully launched into the real world.

Richard Geering is vice president of governance, risk, and compliance at Immuta. He has over 20 years’ experience in the financial services industry, in global leadership roles in risk, sales, and trading in London, New York, and Barbados. Most recently, he was the chief operational risk officer for a global custodian bank. Richard holds a BSc (with honors) in physics from the University of Nottingham.

Adem Efe Gencer develops Apache Kafka and the ecosystem around it and supports their operation at LinkedIn. In particular, he works on the design, development, and maintenance of Cruise Control, a system for alleviating the management overhead of large-scale Kafka clusters. He actively acts as a reviewer for top-tier journals and conferences. He holds a PhD in computer science from Cornell University, where his research has focused on improving the scalability of blockchain technologies. The protocols introduced in his research were adopted by Waves Platform, Aeternity, Cypherium, Enecuum, Ergo Platform, and Legalthings and are actively being developed into other systems. His papers been cited over 500 times. He received a best student paper award in Middleware Conference.

Noah Gift is lecturer and consultant at both the UC Davis Graduate School of Management MSBA Program and the Graduate Data Science Program at Northwestern, where he designs and teaches graduate machine learning, AI, data science courses and consults on machine learning and cloud architecture for students and faculty. These responsibilities including leading a multicloud certification initiative for students. As the founder of Pragmatic AI Labs, he also consults with companies on machine learning, cloud architecture, and CTO-level concerns. In the last 10 years, he’s been responsible for shipping many new products at multiple companies that generated millions of dollars of revenue and had global scale. His previous roles have included CTO, general manager, consulting CTO, consulting chief data scientist, and cloud architect, at companies such as ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios, and Linden Lab. As an SME on machine learning for AWS, he helped created the AWS machine learning certification.

Noah is a Python Software Foundation Fellow, AWS Subject Matter Expert (SME) on machine learning, AWS Certified Solutions Architect and AWS Academy Accredited Instructor, Google Certified Professional Cloud Architect, and Microsoft MTA on Python. He has published close to 100 technical publications, including two books on subjects ranging from cloud machine learning to DevOps, for companies like Forbes, IBM, Red Hat, Microsoft, O’Reilly, and Pearson. He’s also led workshops and talks around the world, for organizations including NASA, PayPal, PyCon, Strata, and Foo Camp. His most recent book is Pragmatic AI: An Introduction to Cloud-Based Machine Learning (Pearson), and his most recent video series is Essential Machine Learning and AI with Python and Jupyter Notebook LiveLessons. He holds an MBA from UC Davis, an MS in computer information systems from Cal State Los Angeles, and a BS in nutritional science from Cal Poly San Luis Obispo.

Benjamin Glicksberg is a postdoctoral scholar in the lab of Atul Butte in the Bakar Computational Health Sciences Institute at the University of California, San Francisco. His work involves utilizing state-of-the-art computational methods, including artificial intelligence algorithms, on bio- and clinical informatics frameworks to make discoveries to push forward precision medicine. His work often ties together multiomic data types ranging from genomics to clinical data in the form of electronic health records (EHR). He’s also built software, tools, and applications for interacting with and visualizing EHR data across patients in the UC Health system, with a particular emphasis on interoperable common data model formats. He holds a PhD from the Icahn School of Medicine at Mount Sinai.

Sean Glover is a senior software engineer on the Fast Data Platform team at Lightbend, where he specializes in Kubernetes, Apache Kafka, and its ecosystem. Sean enjoys building fast data platforms and reactive distributed systems and contributing to open source projects.

Sharad Goel is an assistant professor in the Department of Management Science and Engineering at Stanford University and the founder and director of the Stanford Computational Policy Lab. He also holds courtesy appointments in the Computer Science and Sociology Departments and the Law School. Previously, he was a senior researcher at Yahoo and Microsoft in New York City. In his research, Sharad looks at public policy through the lens of computer science, bringing a new, computational perspective to a diverse range of contemporary social issues, including policing, incarceration, and elections. He holds a PhD in applied mathematics from Cornell University.

Shafi Goldwasser is the RSA Professor of Electrical Engineering and Computer Science at MIT and the incoming director of the Simons Institute for the Theory of Computing at UC Berkeley. She is also a professor of computer science and applied mathematics at the Weizmann Institute of Science in Israel. Shafi’s pioneering contributions include the introduction of probabilistic encryption, interactive zero-knowledge protocols, elliptic curve primality testings, hardness of approximation proofs for combinatorial problems, and combinatorial property testing. She was the recipient of the ACM Turing Award for 2012, the Gödel Prize in 1993 and another in 2001, the ACM Grace Murray Hopper award in 1996, the RSA Award in Mathematics in 1998, the ACM Athena Award for Women in Computer Science in 2008, the Benjamin Franklin Medal in 2010, the IEEE Emanuel R. Piore Award in 2011, the Simons Foundation Investigator Award in 2012, and the BBVA Foundation Frontiers of Knowledge Award in 2018. She’s a member of the NAS, NAE, AAAS, the Russian Academy of Science, the Israeli Academy of Science, and the London Royal Mathematical Society. She a holds honorary degrees from Ben Gurion University, Bar Ilan University, and Haifa University and was recognized with a Berkeley Distinguished Alumnus Award and the Barnard College Medal of Distinction. Shafi holds a BS in applied mathematics from Carnegie Mellon University and an MS and PhD in computer science from the University of California, Berkeley.

Thomas Goolsby is data and analytics director at USAA, where he focuses on member interaction data and research with universities to help provide new insights and build pipelines of talent.

Alex Gorbachev is the head of enterprise data science at Pythian. His mission is to help clients around the world build applied AI solutions and democratize data science. Over the course of his 12 years at Pythian, Alex has held many roles, including chief technology officer and chief digital officer. His deep technological roots and industry vision has helped Pythian get to the forefront of the emerging cloud and data markets. Alex is a highly sought-after speaker at industry conferences and user groups around the world. His past accomplishments include achieving the prestigious Oracle ACE Director designation from Oracle and being named “Big Data Champion” by Cloudera.

Martin Gorner is a developer advocate at Google, where he focuses on parallel processing and machine learning. Martin is passionate about science, technology, coding, algorithms, and everything in between. He spent his first engineering years in the Computer Architecture Group of ST Microelectronics, then spent the next 11 years shaping the nascent ebook market at Mobipocket, which later became the software part of the Amazon Kindle and its mobile variants. He’s the author of the successful TensorFlow Without a PhD series. He graduated from Mines Paris Tech.

Denise Koessler Gosnell is the chief data officer at DataStax, where she applies her experiences as a machine learning and graph data practitioner to make more informed decisions with data. Her career centers on her passion for examining, applying, and advocating the applications of graph data. She has patented, built, published, and spoken on dozens of topics related to graph theory, graph algorithms, graph databases, and applications of graph data across all industry verticals. Previously, Denise created and led the global graph practice, a team that builds some of the largest distributed graph applications in the world at DataStax, and she was in the healthcare industry, where she contributed to software solutions for permissioned blockchains, machine learning applications of graph analytics, and data science. Denise earned her PhD in computer science from the University of Tennessee as an NSF fellow. Her research coined the concept “social fingerprinting” by applying graph algorithms to predict user identity from social media interactions.

Bill Graham is an architect on the data platform team at Lyft. Bill’s primary area of focus is on data processing applications and analytics infrastructure. Previously, he was a staff engineer on the data platform team at Twitter, where he built streaming compute, interactive query, batch query, ETL, and data management systems; a principal engineer at CBS Interactive and CNET Networks, where he developed ad targeting and content publishing infrastructure; and a senior engineer at Logitech focusing on webcam streaming and messaging applications. He’s contributed to a number of open source projects, including Apache HBase, Apache Hive, and Presto and is an Apache Pig and Apache Heron (incubating) PMC member.

Trevor Grant is a computer nerd at IBM, an Apache Software Foundation Member, and is involved in multiple projects such as Mahout, Streams, and SDAP-incubating, just to name a few. He speaks about computer stuff internationally. He’s taken numerous classes in stand-up and improv comedy to make his talks more pleasant for you—the listener. He holds an MS in applied math and an MBA from Illinois State University.

Brian Patrick Green is the director of technology ethics at the Markkula Center for Applied Ethics at Santa Clara University. His responsibilities include representing the center at the Partnership on Artificial Intelligence to Benefit People and Society, speaking and publishing on AI ethics as well as various other topics in ethics and technology, and coordinating the center’s partnership with the Tech Museum of Innovation in San Jose. Brian also reviews and evaluates applications to the center’s Hackworth grant program, which awards funding to SCU faculty, staff, and students for work in applied ethics; coordinates the Technology and Ethics Faculty Group; helps coach and coordinate the university’s Ethics Bowl team; works with the center’s Environmental Ethics Fellows; and assists with several other initiatives. In addition, he teaches engineering ethics in the Graduate School of Engineering. Brian’s background includes doctoral and master’s degrees in ethics and social theory from the Graduate Theological Union in Berkeley and an undergraduate degree in genetics from the University of California, Davis. He has conducted molecular biology research in both academic and industrial settings, and between college and graduate school, he served for two years in the Jesuit Volunteers International, teaching high school in the Marshall Islands. His research interests include multiple topics in the ethics of technology, such as AI and ethics, the ethics of space exploration and use, the ethics of technological manipulation of humans, the ethics of mitigation of and adaptation toward risky emerging technologies, and various aspects of the impact of technology and engineering on human life and society, including the relationship of technology and religion (particularly the Catholic Church). Many of his writings can be found at his academia.edu page.

Michael Gregory leads the field team for machine learning at Cloudera helping organizations derive business value from machine learning. Michael has more than 20 years of experience building, selling, implementing, and supporting large-scale data management solutions at Sun Microsystems, Oracle, Teradata, and Hortonworks and has seen and evangelized the power of data to transform organizations and industries from automotive to telco and public sector to manufacturing.

Mark Grover is a product manager at Lyft. Mark’s a committer on Apache Bigtop, a committer and PPMC member on Apache Spot (incubating), and a committer and PMC member on Apache Sentry. He’s also contributed to a number of open source projects, including Apache Hadoop, Apache Hive, Apache Sqoop, and Apache Flume. He’s a coauthor of Hadoop Application Architectures and wrote a section in Programming Hive. Mark is a sought-after speaker on topics related to big data. He occasionally blogs on topics related to technology.

Sijie Guo is the founder and CEO of StreamNative, a data infrastructure startup offering a cloud native event streaming platform based on Apache Pulsar for enterprises. He’s also the vice president of Apache BookKeeper and a PMC member of Apache Pulsar. Previously, he was the tech lead for the Messaging Group at Twitter and worked on push notification infrastructure at Yahoo.

Bulbul Gupta is the Founding Advisor of Socos Labs, a think tank designing Augmented Intelligence to maximize human potential through “mad science research,” advance human-centered policy, ethical AI; advise startups, companies, governments on using ethical AI. She is the former head of Entrepreneurship & Market-Based Approaches at the Clinton Global Initiative; and Global Entrepreneurship Policy Advisor, Clinton Campaign ‘16. She serves as a family office advisor; and Board Member & Investment Committees for Upaya Social Ventures, and Pacific Community Ventures. Bulbul is an Adjunct Lecturer at Hult International Business School, NYU Wagner School Corporate Social Innovation programs; and a Speaker & Coach at Singularity Ventures, 500 Startups, Village Capital, Women’s Startup Lab. She is on MacArthur Foundation’s Place-Based Investing, and the Global Social Good/G8 Impact Investing task forces. She has a Masters in Public Policy & Economics from the University of Michigan, is a “conscious capitalist,” an immigrant daughter of Indian tech entrepreneurs, and lives in Palo Alto w/her Jedi daughters.

Bulbul has spent her 18-yr career at the intersection of responsible investing, technology & venture, and public policy, working with globally-minded entrepreneurs & conscious CEOs, to maximize for people & social impact. She is passionate about helping founders realize their visions for a better world, advancing technology innovation & investment in under-estimated people & places, ensuring inclusion & human-centered design. She has helped launch and operationalize a number of innovation strategies, in large and startup organizations, including change management, talent development, learning, aligning resources strategically.

Chunky Gupta is a member of the technical staff at Mist Systems, where he works on scaling the company’s cloud infrastructure. Previously, he was a software engineer at Yelp, where he developed an autoscaling engine, FleetMiser, to intelligently autoscale Yelp’s Mesos cluster, saving millions of dollars. He also scaled Yelp’s in-house distributed and reliable task runner, Seagull (which he wrote about for the Yelp engineering blog). Before that, he built a Hadoop-based data warehouse system at Vizury. He gave a talk on FleetMiser at re:Invent 2016. Chunky holds an MS in computer science from Texas A&M University.

Kapil Gupta is a data science leader at Airbnb in San Francisco, where he leads the data science team focused on launching new travel verticals like Experiences and establishing Airbnb as an end-to-end travel platform. In his time at the company, he has worked on many challenging machine learning and personalization problems in search, pricing, and risk. Previously, he worked at PayPal and Duff & Phelps. He holds a PhD in operations research from Georgia Tech and a BTech from the Indian Institute of Technology (IIT), Madras.

Sonal Gupta is a research scientist at Facebook working on conversational AI systems. Previously, she developed deep learning natural language understanding models for conversational AI systems at Viv, a startup later acquired by Samsung. She holds a PhD on weakly supervised and interpretable information extraction from Stanford University and a master’s degree on combining language and vision modes for information extraction at the University of Texas at Austin.

Juan Paulo Gutierrez is a senior software engineer at Rakuten, where he leads data architecture, data engineering, and data visualization teams. Paulo contributes to open source projects through code, documentation, feature requests, and discussions. Previously, he was the product development lead for Media Links’s network management software.

Barkha Gvalani is a partner at GV (formerly known as Google Ventures), where she works on investing operations, product management, and analytics and helps portfolio companies scale their operations through analytics, data warehousing, and business intelligence. Previously, Barkha helped solve hard data problems for Google’s ads and hardware finance teams and was chief of staff on the team overseeing Google’s financial systems strategy. Before that, she worked at Tata Consultancy Services, where she specialized in the leasing business and consulted for GE Commercial Finance.

John Haddad is vice president at Informatica, where he runs product and technical marketing for the Big Data, Enterprise Data Catalog and Cloud/Hybrid data management product portfolios. He has over 25 years’ experience developing and marketing enterprise software, focusing on enterprise cloud data management over the last 10 years. Previously, John held various positions in product marketing, R&D, and management at Oracle and Right Hemisphere (acquired by SAP). John holds an AB in applied mathematics from UC Berkeley.

Patrick Hall is principle scientist at bnh.ai, a boutique law firm focused on AI and analytics; a senior director of product at H2O.ai, a leading Silicon Valley machine learning software company; and a lecturer in the Department of Decision Sciences at George Washington University, where he teaches graduate classes in data mining and machine learning.

At both bnh.ai and H2O.ai, he works to mitigate AI risks and advance the responsible practice of machine learning. Previously, Patrick held global customer-facing and R&D research roles at SAS. He holds multiple patents in automated market segmentation using clustering and deep neural networks. Patrick is the 11th person worldwide to become a Cloudera Certified Data Scientist. He studied computational chemistry at the University of Illinois before graduating from the Institute for Advanced Analytics at North Carolina State University.

Melinda Han Williams is the chief data scientist at Dstillery. Before joining the ad tech industry, Melinda worked as a physicist developing third generation photovoltaics and studying electronic transport in nanostructured graphene devices. Her peer-reviewed journal publications have been cited over 8,000 times. Melinda holds bachelor’s degrees in applied math and engineering physics from the University of California at Berkeley and a PhD in applied physics with distinction from Columbia University, where she held a National Science Foundation Graduate Research Fellowship.

Vikas Hardia is a BI and Hadoop expert at Kyvos, helping the business with data insights on big data platforms.

Roy Hasson is a Sr Manager of Global Business Development for Analytics and Data Lakes at Amazon Web Services, where he helps transform organizations using data. Roy serves as an expert resource on big data architectures, data lakes and machine learning. Previously at AWS, Roy served as a Technical Account Manager leading strategy and supporting implementation of data architectures with select customers. Prior to AWS, Roy spent 15 years working with tier 1 service providers to design and deploy large data and telephone network systems.

Janet Haven is the executive director of Data & Society. Previously, she was Data & Society’s director of programs and strategy; spent more than a decade at the Open Society Foundations, where she oversaw funding strategies and grant making related to technology’s role in supporting and advancing civil society, particularly in the areas of human rights and governance and accountability; and started her career in technology startups in central Europe, participating in several successful acquisitions. She sits on the board of the Public Lab for Open Science and Technology and advises a range of nonprofit organizations. Janet holds an MA from the University of Virginia and a BA from Amherst College.

Yaron Haviv is CTO at iguazio. Yaron is a serial entrepreneur with deep technological experience in the fields of big data, cloud, storage and networking. Previously, he was the vice president of data center solutions at Mellanox, where he led technology innovation, software development, and solution integrations, and the CTO and vice president of R&D at Voltaire, a high-performance computing, I/O, and networking company. Yaron is a CNCF member and one of the authors in the CNCF working group.

Terry He is a senior director of engineering at MapR, where he manages MapR’s Hadoop and ecosystem engineering teams and leads the company’s AI/ML initiatives.

Norris Heintzelman is a senior research and data scientist with 19 years’ real-world experience converting data into knowledge—that is, 19 years’ experience in many areas of natural language processing, knowledge systems, cleaning and normalizing messy data, and rigorous accuracy measurement. Norris has published several papers in the fields of health informatics and general knowledge management. She has worked for Lockheed Martin for a very long time, in multiple business areas, from public sector contracts to advanced R&D to internal business process support. An alumna of both Temple University and the University of Pennsylvania, she lives in Wilmington, Delaware, with her husband, two daughters, and two cats. She likes to eat and talk about food.

Michael Ho is a software engineer at Cloudera. He has worked on various parts of the Apache Impala query execution engine such as reducing codegen time, overhauling expressions evaluation, and most recently, making Impala more scalable. Before Cloudera, Michael used to build hypervisors and VMMs at VMware.

Chris Holdgraf is a data science fellow at the Berkeley Institute for Data Science and a community architect at the Data Science Education Program at UC Berkeley. His background is in cognitive and computational neuroscience, where he used predictive models to understand the auditory system in the human brain. He’s interested in the boundary between technology, open source software, and scientific workflows, as well as creating new pathways for this kind of work in science and the academy. He’s a core member of Project Jupyter, specifically working with JupyterHub and Binder, two open source projects that make it easier for researchers and educators to do their work in the cloud. He works on these core tools, along with research and educational projects that use these tools at Berkeley and in the broader open science community.

Bob Horton is a senior data scientist on the user understanding team at Bing. Bob holds an adjunct faculty appointment in health informatics at the University of San Francisco, where he gives occasional lectures and advises students on data analysis and simulation projects. Previously, he was on the professional services team at Revolution Analytics. Long before becoming a data scientist, he was a regular scientist (with a PhD in biomedical science and molecular biology from the Mayo Clinic). Some time after that, he got an MS in computer science from California State University, Sacramento.

Jeremy Howard is an entrepreneur, business strategist, developer, and educator. Jeremy is a founding researcher at fast.ai, a research institute dedicated to making deep learning more accessible. He is also a Distinguished Research Scientist at the University of San Francisco, a faculty member at Singularity University, and a Young Global Leader with the World Economic Forum. Jeremy’s most recent startup, Enlitic, was the first company to apply deep learning to medicine and was selected one of the world’s top 50 smartest companies by MIT Tech Review two years running. Previously, he was the president and chief scientist at the data science platform Kaggle, where he was the top ranked participant in international machine learning competitions two years running; was the founding CEO of successful Australian startups FastMail and Optimal Decisions Group (acquired by Lexis-Nexis); and spent eight years in management consulting at McKinsey & Co. and AT Kearney. Jeremy has invested in, mentored, and advised many startups and contributed to many open source projects. He has made a number of television and video appearances, including as a regular guest on Australia’s highest-rated breakfast news program, a popular talk on TED.com, and data science and web development tutorials and discussions.

Joel Hron is chief technology officer at ThoughtTrace, where he’s responsible for product innovation and strategy, the development and application of AI and machine learning, and full stack software development. His team is comprised of data scientists, full stack developers, DevOps engineers, quality assurance engineers, and domain experts who all work together to deliver innovative applied AI solutions that function in a highly scalable and reliable way. Previously, he held various engineering and management roles at Anadarko Petroleum Corporation, where he helped develop and shepherd new technologies enabling digital operations, better reservoir characterization, and field development optimization, with a focus on applied data science, artificial intelligence, machine learning, and other big data technologies. He holds a BS in mechanical engineering from TCU and an MS in mechanical engineering from the University of Texas.

Chenhui Hu is a data scientist in the Cloud and AI Division at Microsoft. He works on developing machine learning and big data solutions for internal and external customers. His current interests include time series forecasting, natural language processing, large-scale machine learning, and deep learning. He received his PhD degree from Harvard University with a focus on imaging data mining and signal processing. He has presented his work in many international conferences including O’Reilly AI Conference 2019 and O’Reilly Strata 2019.

Emily Huang is senior manager of the data science team at LinkedIn. Emily has more than 10 years of experience in security data science, customer operation analytics, and data product development across industries including finance, ecommerce, social networks, and SaaS. She’s passionate about translating business problems into qualitative questions, solving them by synthesizing and mining large-scale data, and driving business decisions. She’s also enthusiastic about developing the data science community via mentoring, volunteering, and being an evangelist of data-informed culture for all organizations.

Fabian Hueske is a committer and PMC member of the Apache Flink project. He was one of the three original authors of the Stratosphere research system, from which Apache Flink was forked in 2014. Fabian is a cofounder of Ververica, a Berlin-based startup devoted to fostering Flink, where he works as a software engineer and contributes to Apache Flink. He holds a PhD in computer science from TU Berlin and is currently spending a lot of his time writing a book, Stream Processing with Apache Flink.

Cory Ilo is a computer vision engineer in the Automotive Solutions Group at Intel, where he helps prototype and research the feasibility of various computer vision solutions in relation to privacy, ethics, deep learning, and autonomous vehicles. In his spare time, Cory focuses on his passion for fitness, video games, and wanderlust, in addition to finding ways on how they tie into computer vision.

Mario Inchiosa is a principal software engineer at Microsoft, where he focuses on scalable machine learning and AI. Previously, Mario served as Revolution Analytics’s chief scientist; analytics architect in IBM’s Big Data organization, where he worked on advanced analytics in Hadoop, Teradata, and R; US chief scientist in Netezza Labs, bringing advanced analytics and R integration to Netezza’s SQL-based data warehouse appliances; US chief science officer at NuTech Solutions, a computer science consultancy specializing in simulation, optimization, and data mining; and senior scientist at BiosGroup, a complexity science spin-off of the Santa Fe Institute. Mario holds bachelor’s, master’s, and PhD degrees in physics from Harvard University. He has been awarded four patents and has published over 30 research papers, earning publication of the year and open literature publication excellence awards.

Alex Ingerman is a product manager at Google AI, focusing on federated learning and other privacy-preserving technologies. His mission is to enable all ML practitioners to protect their users’ privacy by default. Previously, Alex worked on ML-as-a-service platforms for developers, web-scale search, content recommendation systems, and immersive data exploration and visualization. Alex lives in Seattle, where as a frequent bike and occasional kayak commuter, he has fully embraced the rain. Alex holds a BS in computer science and an MS in medical engineering.

Akihiro Ishikawa is a software engineer at Cloudera

Maryam Jahanshahi is a research scientist at TapRecruit, a company that is developing software tools to implement evidence-based recruiting. TapRecruit’s research program integrate recent advances in NLP, data science, and decision science to identify robust methods to reduce bias in talent decision making and attract more qualified and diverse candidate pools. In a past life, Maryam was a cancer scientist, where she researched how growing organs “know” they’ve reached the right size. She’s originally from Melbourne, Australia.

Neerav Jain is a technical architect at Walgreens, where he has implemented campaign personalization for all Walgreens customers using Hadoop as well as end-to-end supply chain scorecards with over 120+ TB of data using Hadoop, Kyvos, and Tableau. A senior architect with 15+ years of experience, he has architected and operationalized Hadoop across multiple healthcare and retail organizations and has worked on multiple enterprise data warehouses, including some of the largest in the healthcare industry.

Arif joined Lightspeed in 2008 and focuses primarily on investments in the areas of cloud and datacenter technologies, as well as enterprise mobile and SaaS solutions.

Arif is currently working closely with the teams at Avi Networks, Memoir Systems, Netskope, Nutanix, Pertino Networks, Qubole, Xova Labs and Virtual Instruments. He was also involved in several Lightspeed investments which have had successful exits including Edgespring (acquired by Salesforce.com), IO Turbine (acquired by Fusion-io), RAPsphere (acquired by AppSense) and StreamOnce (acquired by Jive Software).

Prior to joining Lightspeed, Arif worked in the Corporate Business Development group at Cisco Systems where he focused on mergers and acquisitions, strategy, and investments in the Unified Communications, Enterprise Collaboration, Mobile, and SaaS market segments. Before joining Cisco Systems, he was with Novitas Capital, an early-stage venture capital firm.

Earlier in his career, Arif worked in technical development and product management roles at WebTV (acquired by MSFT), Andes Networks (acquired by SUNW), and Sun Microsystems.

Arif is a charter Member and member of the Organizing Committee for the C100, a non-profit, member-driven organization that supports Canadian technology entrepreneurship through mentorship, partnership and investment. He also founded WVP Ventures, a student-run venture capital fund, while in business school.

Arif holds an MBA from the Wharton School, University of Pennsylvania and a BSc in Computer Engineering from the University of Waterloo, Canada.

Michael Johnson is a senior data scientist at Lockheed Martin. He has done data science and analytics in fields including manufacturing optimization, semiconductor reliability, and human resources-focused time series forecasting and simulation. He has recently been focused on how to apply cutting-edge deep learning algorithms to NLP domains.

Theresa Johnson is a product manager for metrics and forecasting products at Airbnb. As a data scientist, she was part of the task force and cross-functional hackathon team at Airbnb that worked to develop the framework for the current antidiscrimination efforts. Theresa is a founding board member of Street Code Academy, a nonprofit dedicated to high-touch technical training for inner city youth, and has been featured in TechCrunch for her commitment to helping early-stage founders raise capital. Theresa is passionate about extending technology access for everyone and finding mission-driven companies that can have an outsized impact on the world. She holds a PhD in aeronautics and astronautics and dual undergraduate degrees in science, technology, and society and computer science, all from Stanford University.

Ken Johnston is the principal data science manager for the Microsoft 360 Business Intelligence Group (M360 BIG). In his time at Microsoft, Ken has shipped many products, including Commerce Server, Office 365, Bing Local and Segments, and Windows, and for two-and-a-half years, he was the director of test excellence. A frequent keynote presenter, trainer, blogger, and author, Ken is a coauthor of How We Test Software at Microsoft and contributing author to Experiences of Test Automation: Case Studies of Software Test Automation. He holds an MBA from the University of Washington. Check out his blog posts on data science management on LinkedIn.

Eric Jonas is a postdoc in the new Berkeley Center for Computational Imaging and RISELab at UC Berkeley EECS working with Ben Recht. His research interests include biological signal acquisition, inverse problems, machine learning, heliophysics, neuroscience, and other exciting ways of exploiting scalable computation to understand the world.

Jowanza Joseph is principal software engineer at One Click Retail. Jowanza’s work is focused on distributed stream processing and distributed data storage.

Yiannis Kanellopoulos has spent the better part of two decades analyzing and evaluating software systems in order to help organizations address any potential risks and flaws related to them. (In his experience, these risks or flaws are always due to human involvement.) With Code4Thought, Yiannis is turning his expertise into democratizing technology by rendering algorithms transparent and helping organizations become accountable. Targeted outcomes of his work include building trust between the organization utilizing the algorithms and those affected by its output and rendering the algorithms more persuasive, since their reasoning will be easier to explain. He’s also a founding member of Orange Grove Patras, a business incubator sponsored by the Dutch Embassy in Greece to promote entrepreneurship and counter youth unemployment. Yiannis holds a PhD in computer science from the University of Manchester.

Holden Karau is a transgender Canadian software engineer working in the bay area. Previously, she worked at IBM, Alpine, Databricks, Google (twice), Foursquare, and Amazon. Holden is the coauthor of Learning Spark, High Performance Spark, and another Spark book that’s a bit more out of date. She’s a committer on the Apache Spark, SystemML, and Mahout projects. When not in San Francisco, Holden speaks internationally about different big data technologies (mostly Spark). She was tricked into the world of big data while trying to improve search and recommendation systems and has long since forgotten her original goal. Outside of work, she enjoys playing with fire, riding scooters, and dancing.

Alon Kaufman is the cofounder and CEO at Duality Technologies. Previously, he was RSA’s global director of data science and innovation, leading data science across the company’s full portfolio. Alon has over 20 years of experience in technology and innovation management in high-tech companies, dealing with various aspects of artificial intelligence. He holds a PhD in computational neuroscience and machine learning from the Hebrew University and an MBA from Tel Aviv University.

Arun Kejariwal is an independent lead engineer. Previously, he was he was a statistical learning principal at Machine Zone (MZ), where he led a team of top-tier researchers and worked on research and development of novel techniques for install-and-click fraud detection and assessing the efficacy of TV campaigns and optimization of marketing campaigns, and his team built novel methods for bot detection, intrusion detection, and real-time anomaly detection; and he developed and open-sourced techniques for anomaly detection and breakout detection at Twitter. His research includes the development of practical and statistically rigorous techniques and methodologies to deliver high performance, availability, and scalability in large-scale distributed clusters. Some of the techniques he helped develop have been presented at international conferences and published in peer-reviewed journals.

Jinchul Kim is a senior software engineer at SK Telecom, where he leads cloud platform development using Kubernetes, Docker, Apache Druid, and Apache Hadoop and designed and implemented a Dockerized DevOps framework. Previously, he was a senior software engineer at SAP Labs working on the SAP HANA in-memory engine. Jinchul is a committer to the Apache Impala project.

Alex Kira is an engineering tech lead at Uber, where he works on the data workflow management team. His team provides a data infrastructure platform for thousands of engineers, data scientists, and city ops, thereby empowering them to own and manage their data pipelines. During his 19-year career, he’s had experience across several software disciplines, including distributed systems, data infrastructure, and full stack development, giving him a holistic systems view of his projects. He holds an undergraduate degree in computer science from the University of Miami and a master’s degree from the Georgia Institute of Technology. In his free time, Alex enjoys hiking around the Bay Area, rock climbing, and traveling internationally.

Tobi Knaup is the cofounder and CTO at Mesosphere, a hybrid cloud platform company that helps companies such as NBCUniversal, Deutsche Telekom, and Royal Caribbean adopt transformative technologies like machine learning and real-time analytics with ease. He was one of the first engineers and tech lead at Airbnb, where he wrote large parts of the company’s infrastructure, including its search and fraud prediction services, and helped scale the site to millions of users and build a world-class engineering team. Tobi is the main author of Marathon, Mesosphere’s container orchestrator.

Michael Kohs is a product manager at Cloudera.

Jari Koister is the vice president of product and technology at FICO. He also teaches in the Data Science Program at UC Berkeley. Previously, he has, among other things, led the development of Chatter, Salesforce’s social enterprise application and platform; founded and served as CTO at Groupswim.com, an early social enterprise collaboration company (acquired by Salesforce); founded and served as CSO and CTO at Qrodo.com, an elastic platform for broadcasting sports events live on the internet; led the development of CommerceOne’s flagship product MarketSite; and led research in computer languages and distributed computing at Ericsson Labs and Hewlett-Packard Laboratories. Jari holds a PhD in computer science from the Royal Institute of Technology, Stockholm, Sweden.

Jing (Nicole) Kong is a data scientist at Office Depot, where she deals with big data and transforms data and models into products and service that drive business. She’s experienced with a number of different machine learning and deep learning models.

Jing（Nicole）是一位数据科学家，拥有构建不同的机器学习/深度学习模型、处理大数据以及将数据/模型转换为推动业务发展的产品和服务的经验。

Gabor Kotalik is a big data project lead at Deutsche Telekom, where he’s responsible for continuous improvement of customer analytics and machine learning solutions for the commercial roaming business. He has more than 10 years of experience in business intelligence and advanced analytics focusing on using insights and enabling data-driven business decisions.

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Chi-Yi Kuan is director of data science at LinkedIn. He has over 15 years of extensive experience applying big data analytics, business intelligence, risk and fraud management, data science, and marketing mix modeling across various business domains (social network, ecommerce, SaaS, and consulting) at both Fortune 500 firms and startups. Chi-Yi is dedicated to helping organizations become more data driven and profitable. He combines deep expertise in analytics and data science with business acumen and dynamic technology leadership.

Aleksandra Kudriashova leads data product integration at Astro Digital, a platform for fast and easy access to satellite imagery. Previously, she was a cofounder of ImageAiry, an online marketplace for satellite imaging services, and worked on B2B software solutions at Dell. Her interests are open source, big data, and business intelligence. She honed her computer science and technical leadership expertise at MIT.

Abhishek Kumar is a senior manager of data science in Publicis Sapient’s India office, where he looks after scaling up the data science practice by applying machine learning and deep learning techniques to domains such as retail, ecommerce, marketing, and operations. Abhishek is an experienced data science professional and technical team lead specializing in building and managing data products from conceptualization to the deployment phase and interested in solving challenging machine learning problems. Previously, he worked in the R&D center for the largest power-generation company in India on various machine learning projects involving predictive modeling, forecasting, optimization, and anomaly detection and led the center’s data science team in the development and deployment of data science-related projects in several thermal and solar power plant sites. Abhishek is a technical writer and blogger as well as a Pluralsight author and has created several data science courses. He’s also a regular speaker at various national and international conferences and universities. Abhishek holds a master’s degree in information and data science from the University of California, Berkeley. Abhishek has spoken at past O’Reilly conferences, including Strata 2019, Strata 2018, and AI 2019.

Arun Kumar is an assistant professor in the Department of Computer Science and Engineering at the University of California, San Diego. He’s a member of the Database Lab and CNS and an affiliate member of the AI Group. His primary research interests are in data management and systems for machine learning- and artificial intelligence-based data analytics. Systems and ideas based on his research have been released as part of the MADlib open source library, shipped as part of products from EMC, Oracle, Cloudera, and IBM, and used internally by Facebook, LogicBlox, Microsoft, and other companies. He’s a recipient of the ACM SIGMOD 2014 Best Paper Award, the 2016 Graduate Student Research Award for the best dissertation research in UW-Madison CS, and a 2016 Google Faculty Research Award.

Rakesh Kumar is a software engineer on the pricing team at Lyft. He started his career as an embedded software engineer for mobile devices; later he moved to server-side engineer to tackle bigger challenges in distributed systems. His interests include machine learning and streaming systems.

Santosh Kumar is a senior product manager at Cloudera, where he leads SDX, Cloudera’s shared data experience offering. Previously, he was a data scientist at Facebook and a software engineer at Yahoo and Akamai. He holds a BS in computer science from IIT Kanpur, India, and an MBA from INSEAD, France.

Kumar Sricharan is a principal data scientist responsible for leading Intuit’s Machine Learning (ML) Research Group. His team focuses on cutting-edge ML problems and applications for financial artificial intelligence, combining financial domain knowledge with information in data to produce more accurate and explainable systems. Projects include extraction of information from financial documents, chatbots for financial conversations, mining tax forms to enable compliance, understanding transactions to power financial advice, and financial forecasting. Previously, he spent five years at Xerox PARC as a senior research scientist and program manager for self-learning systems. During his time at PARC, Kumar led a team focused on building learning algorithms that can exploit rich feedback in conjunction with unlabeled data to overcome the need for prohibitively large numbers of labeled examples and make these systems explainable. His other research interests include anomaly detection for large, unstructured data and nonparametric large sample estimation, and his research has resulted in nearly 30 papers in refereed conferences and journals and several accompanying patents. He’s an active member of the academic community and has served as a reviewer for multiple conferences and journals. He has also participated in several DARPA research projects, including the ADAMS program for detecting insider threat and XAI for building explainable AI agents. Kumar holds a PhD in electrical engineering from the University of Michigan.

Lauren Kunze is the CEO of Pandorabots, a leading chatbot platform that powers conversational AI software for hundreds of thousands of developers and top global brands. She’s an expert on state-of-the-art solutions for hard AI problems like natural language understanding and generation with respect to the larger AI ecosystem. Lauren built her first chatbot at age 15, and she speaks and writes frequently about chatbots and AI at conferences like Mobile World Congress and South by Southwest and for publications like TechCrunch and Quartz. Pandorabots has been quoted or covered in outlets like the Wall Street Journal, the BBC, the Guardian, Wired, Quartz, RadioLab, TechCrunch, Reuters, the New Yorker, and the New York Times Magazine. Lauren is the author of four novels published by HarperCollins as well as scripts for film and television. She holds a degree from Harvard in literature and language and neuroscience.

Latheef Syed is head of analytics at Verizon. An executive thought leader, Latheef leads the company’s enterprise data science and analytical teams to enable predictive and prescriptive analytics through advance deep learning techniques both on-premises and in the cloud. He’s adept at delivering industry best practices by building a system of insights framework that leverages big data and AI platforms with integrated business solutions. He has 20+ years’ experience leading enterprise analytical application development and systems integration and is an expert at program management at all levels of the business.

JoLynn Lavin is a manager of decision sciences and analytics at General Mills, where she leads a team of analysts focused on unleashing the power of data to drive consumer-led decision making. Previously, JoLynn was a loyalty marketing consultant helping clients acquire, retain, and build profitable relationships with their customers across virtually every industry. JoLynn holds a master’s degree in agricultural and consumer economics from the University of Illinois at Champaign-Urbana.

Francesca Lazzeri is a senior machine learning scientist at Microsoft on the cloud advocacy team and an expert in big data technology innovations and the applications of machine learning-based solutions to real-world problems. Her research has spanned the areas of machine learning, statistical modeling, time series econometrics and forecasting, and a range of industries—energy, oil and gas, retail, aerospace, healthcare, and professional services. Previously, she was a research fellow in business economics at Harvard Business School, where she performed statistical and econometric analysis within the technology and operations management unit. At Harvard, she worked on multiple patent, publication and social network data-driven projects to investigate and measure the impact of external knowledge networks on companies’ competitiveness and innovation. Francesca periodically teaches applied analytics and machine learning classes at universities and research institutions around the world. She’s a data science mentor for PhD and postdoc students at the Massachusetts Institute of Technology and speaker at academic and industry conferences—where she shares her knowledge and passion for AI, machine learning, and coding.

Julien Le Dem is a principal engineer at WeWork. He’s also the coauthor of Apache Parquet and the PMC chair of the project, and he’s a committer and PMC member on Apache Pig, Apache Arrow, and a few other projects. Previously, he was an architect at Dremio; tech lead for Twitter’s data processing tools, where he also obtained a two-character Twitter handle (@J_); and a principal engineer and tech lead working on content platforms at Yahoo, where he received his Hadoop initiation. His French accent makes his talks particularly attractive.

Mike Lee Williams is a research engineer at Cloudera Fast Forward Labs, where he builds prototypes that bring the latest ideas in machine learning and AI to life and helps Cloudera’s customers understand how to make use of these new technologies. Mike holds a PhD in astrophysics from Oxford.

Christopher Lennan is a senior data scientist at idealo.de, where he works on computer vision problems to improve the product search experience. In previous positions, he applied machine learning methods to fMRI and financial data. Christopher holds a master’s degree in statistics from Humboldt Universität Berlin.

Franck Leveneur is data service technical lead at Wag!. Franck has spent the last 16 years working as a DBA and data architect across various technology companies, including Davita, TrueCar, Rubicon Project, and ZipRecruiter. He’s an expert in MySQL database design and architecture, performance tuning, capacity planning, and scalability in a multitier, high-volume production database ecosystems. He also teaches data management at UCLA Anderson.

Jimmy Li is a versatile principal developer at Atlassian. He has a breadth of experience from working in a variety of teams and countries, and he’s been part of several key initiatives ranging from single sign-on to segmentation and targeted in-product messaging. Most recently, he was the technical lead on an initiative to change Atlassian into a more data-driven organisation by transforming the company’s behavioural analytics solution.

Tianhui Michael Li is the founder and president of the Data Incubator, a data science training and placement firm. Michael bootstrapped the company and navigated it to a successful sale to the Pragmatic Institute. Previously, he headed monetization data science at Foursquare and has worked at Google, Andreessen Horowitz, JPMorgan, and D.E. Shaw. He’s a regular contributor to the Wall Street Journal, TechCrunch, Wired, Fast Company, Harvard Business Review, MIT Sloan Management Review, Entrepreneur, VentureBeat, TechTarget, and O’Reilly. Michael was a postdoc at Cornell, a PhD at Princeton, and a Marshall Scholar in Cambridge.

Tech lead of messaging system in zhaopin.com, Apache Pulsar Committer.

Tommy Li is a software developer at IBM focusing on cloud, container, and infrastructure technology. He’s worked on various developer journeys that provide use cases on cloud-computing solutions, such as Kubernetes, microservices, and hybrid cloud deployments. He’s passionate about machine learning and big data.

Xiao Li is a software engineer, Apache Spark committer, and PMC member at Databricks. His main interests are Spark SQL, data replication, and data integration. Previously, he was an IBM master inventor and an expert on asynchronous database replication and consistency verification. He holds a PhD from the University of Florida.

Yang Li is the cofounder and CTO at Kyligence and a cocreator, PMC member, tech lead, and architect for Apache Kylin, focusing on big data analysis, parallel computation, data indices, relational algebra, approximation algorithms, and other technologies. Yang was a senior architect in the Analytic Data Infrastructure Department at eBay; a tech lead for IBM InfoSphere BigInsights, where he was responsible for the Hadoop open source platform and was recognized with the Outstanding Technical Achievement Award; and a vice president at Morgan Stanley, responsible for the global regulatory reporting platform.

Yue Li is a cofounder at MemVerge, where together with his colleagues, he’s developing the company’s core technologies. Previously, he was a senior postdoctoral fellow at the California Institute of Technology. He has extensive research experience on both theoretical and experimental aspects of algorithms for nonvolatile memories. Yue holds a PhD in computer science from Texas A&M University and a bachelor’s degree in computer science from Huazhong University of Science & Technology.

Sam Lightstone is CTO for data at IBM, an IBM Fellow, and a Master Inventor in the IBM Data and AI Group. He leads a number of technical teams in product development for relational databases, data warehousing and big data, cloud computing, analytics for IoT, data virtualization, data movement, and machine learning. He cofounded the IEEE Data Engineering Workgroup on Self-Managing Database Systems. Sam has more than 65 patents issued and pending and has authored over 30 papers and four books, which have been translated into Chinese, Japanese, and Spanish. In his spare time, he’s an avid guitar player and fencer.

Di Lin is a senior data engineer on the infrastructure and information security team at Netflix, where he focuses on building and scaling complex data systems to help infrastructure teams improve reliability and efficiency. Previously, he was a data engineer at Facebook, where he built company-wide data products related to identity and subscriber growth.

Girish Lingappa is a senior software engineer at Netflix.

Jorge A. Lopez works in big data solutions at Amazon Web Services. Jorge has more than 15 years of business intelligence and DI experience. He enjoys intelligent design and engaging storytelling and is passionate about data, music, and nature.

Ben Lorica is the chief data scientist at O’Reilly. Ben has applied business intelligence, data mining, machine learning, and statistical analysis in a variety of settings, including direct marketing, consumer and market research, targeted advertising, text mining, and financial engineering. His background includes stints with an investment management company, internet startups, and financial services.

Neng Lu is a software engineer at Twitter, where he is the core member of Twitter’s real-time compute team and the core committer to the Apache Heron project (incubating). He has a broad interest in distributed systems and real-time analytics and has worked on Twitter’s key-value storage system, Manhattan; its monitoring system, Cuckoo; and its real-time processing system, Heron. He holds an MS in CS from UCLA and a bachelor’s degree in CS from Zhejiang University.

Boris Lublinsky is a principal architect at Lightbend, where he specializes in big data, stream processing, and services. Boris has over 30 years’ experience in enterprise architecture. Previously, he was responsible for setting architectural direction, conducting architecture assessments, and creating and executing architectural road maps in fields such as big data (Hadoop-based) solutions, service-oriented architecture (SOA), business process management (BPM), and enterprise application integration (EAI). Boris is the coauthor of Applied SOA: Service-Oriented Architecture and Design Strategies, Professional Hadoop Solutions, and Serving Machine Learning Models. He’s also cofounder of and frequent speaker at several Chicago user groups.

Patrick Lucey is the chief scientist of artificial intelligence at Stats Perform, where his goal is to maximize the value of the 35+ years worth of sports data. His main research interests are in artificial intelligence and interactive machine learning in sporting domains. Previously, Patrick spent five years at Disney Research, where he conducted research into automatic sports broadcasting using large amounts of spatiotemporal tracking data, and was a postdoctoral researcher at the Robotics Institute at Carnegie Mellon University and the Department of Psychology at the University of Pittsburgh, conducting research on automatic facial expression recognition. He holds a BEng (EE) from the University of Southern Queensland and a PhD from QUT, Australia. He was a coauthor of the best paper at the 2016 MIT Sloan Sports Analytics Conference and in 2017 and 2018 was coauthor of best paper runner-up at the same conference. Patrick has also won best paper awards at the INTERSPEECH (2007) and the Winter Conference on Applications of Computer Vision (WACV) (2014) international conferences.

Adrian Lungu is a computer scientist at Adobe working with Audience Manager, a leading solution in the DMP market. He’s been focused on the company’s Cassandra clusters ever since he joined the team, trying to build a scalable architecture that would keep up with the exponential growth of the product. Adrian holds a degree in computer science and engineering from Politehnica University of Bucharest as well as a DataStax Certified Apache Cassandra Professional certification.

Zhenxiao Luo is leading Interactive Query Engines team at Twitter, where he focuses on Druid, Presto, Spark, and Hive. Before joining Twitter, Zhenxiao was running Interactive Analytics team at Uber. He has big data experience at Netflix, Facebook, Cloudera, and Vertica. Zhenxiao is Committer and Technical Steering Committee(TSC) member of Presto. He holds a master’s degree from the University of Wisconsin-Madison and a bachelor’s degree from Fudan University.

Mark Madsen is a Fellow at Teradata, where he’s responsible for understanding, forecasting, and defining analytics ecosystems and architectures. Previously, he was CEO of Third Nature, where he advised companies on data strategy and technology planning, and vendors on product management. Mark has designed analysis, machine learning, data collection, and data management infrastructure for companies worldwide.

Ted Malaska is a director of enterprise architecture at Capital One. Previously, he was the director of engineering in the Global Insight Department at Blizzard; principal solutions architect at Cloudera, helping clients find success with the Hadoop ecosystem; and a lead architect at the Financial Industry Regulatory Authority (FINRA). He has contributed code to Apache Flume, Apache Avro, Apache Yarn, Apache HDFS, Apache Spark, Apache Sqoop, and many more. Ted is a coauthor of Hadoop Application Architectures, a frequent speaker at many conferences, and a frequent blogger on data architectures.

Scott Mcclellan is CTO at PRGX. A creative, results-driven technology leader, Scott is a change agent and problem solver with a passion for technology. He’s skilled in grasping and explaining the big picture and conceptualizing, developing, and implementing solutions. Scott has substantial experience working with business leaders and C-level executives. Previously, he was chief technologist and VP of engineering for Hewlett-Packard’s cloud services and for scalable computing, where he set technical direction for the company’s scalable computing business and introduced new products focused on cloud service providers and high-performance computing customers.

Prakhar Mehrotra is senior director of machine learning for retail data science at Walmart Labs, where he overseas the research and development of pricing, assortment, replenishment, and planning algorithms to help merchants take smarter decisions. Previously, he was head of data science for finance at Uber, where he led a global team of data scientists and data analysts spread across Amsterdam, Hyderabad, and San Francisco in the research and development of machine learning algorithms related to financial forecasting (supply and demand), budget planning, and economic simulations for autonomous vehicles. He also worked on research and development related to payment analytics and treasury financial simulations. Before that, he was a senior data scientist on the sales and monetization team at Twitter. He holds an advanced engineering degree in aeronautics from California Institute of Technology (Caltech) and a dual master’s degree in aeronautics and applied mechanics from École Polytechnique, Paris, and Caltech. He is a peer reviewer for CVPR, ICCV, and AAMAS and has given numerous invited talks including as a keynote speaker at the EARL conference, the Toronto Machine Learning Summit, Deep Learning Summit, the NYU Center for Data Science, and the Wharton Technology Conference. He also chaired the session on forecasting at a 2017 international symposium on forecasting in Australia and was a judge for risk and intelligence at the European Fintech Awards in Brussels.

Jon Merriman is a senior software engineer and researcher at Verint Intelligent Self-Service, where he works on core natural language understanding capabilities for dialogue systems. His primary focus is on algorithms and machine learning theory for text and speech analysis.

Jake Metcalf is a technology ethics researcher and consultant specializing in data analytics and artificial intelligence. He’s a researcher at Data & Society on an NSF-funded multisite project, Pervasive Data Ethics for Computational Research (PERVADE), where he is studying how data ethics practices are emerging in environments that have not previously grappled with research ethics, such as industry, conference committees, and civil society organizations. He’s also exploring how design practices can successfully integrate ethical values and principles. Jake runs consulting firm Ethical Resolve, which provides clients with a range of ethics services, helping them make well-informed, consistent, actionable, and timely business decisions that reflect their values. He lives among the redwoods of the Santa Cruz mountains.

Omoju Miller is a machine learning engineer at GitHub. Omoju has over a decade of experience in computational intelligence. Apart from her work in AI, she has co-led the nonprofit investment in computer science education at Google and served as a volunteer advisor to the Obama administration’s White House Presidential Innovation Fellows. She is a member of the World Economic Forum Expert Network in AI. Omoju holds a PhD from UC Berkeley.

Patrick Miller is a data scientist at Civis Analytics specializing in survey data analysis, causal inference, and production R. Patrick holds a PhD in quantitative psychology, where he studied the applications of machine learning to analysis psychological and behavioral data. You can usually find him at his desk drinking tea and listening to Sufjan Stevens.

Siamac Mirzaie is a senior analytics engineer at Netflix, where he builds end-to-end anomaly detection systems for corporate security. Siamac is an applied machine learning practitioner in the security space. Previously, he was a data scientist at Facebook and director of analytics at Everquote. He holds a master’s degree in EECS from Ecole Supérieure d’Electricité and in financial engineering from the University of Michigan.

Piero Molino is a senior research scientist at Uber AI, where he focuses on machine learning for language and dialogue. Previously, he founded QuestionCube, a startup that built a framework for semantic search and QA, and worked on learning to rank at Yahoo Labs in Barcelona, on natural language processing with deep learning at IBM Watson in New York, and on grounded language understanding at Geometric Intelligence (acquired by Uber). Piero holds a PhD on question answering from the University of Bari, Italy.

Daniel Monteiro works on the Market Regulation Technology Department at FINRA, where he’s the principal developer of the Surveillance Review and Feedback visualization tool. In his 15 years of software development experience, Daniel has developed solutions for various business areas.

Kevin Moore is a senior data scientist at Salesforce, where he works on automated machine learning pipelines to generate and deploy customized models for a wide variety of customers and use cases. He holds a PhD in astrophysics and previously worked on modeling how stars evolve and eventually explode. When not stirring piles of linear algebra, he can usually be found snowboarding, brewing beer, or gaming.

Emanuel Moss is a doctoral candidate in anthropology at the CUNY Graduate Center, where he studies data science, machine learning, and artificial intelligence from an ethnographic perspective, focusing on the role of technologists as producers of knowledge and the ethical, economic, and cultural aspects of their work. He’s also a research analyst at Data & Society, where studies issues of fairness and accountability in machine learning, and a research assistant on the Pervasive Data Ethics for Computational Research (PERVADE) project. Emanuel holds a BA from the University of Illinois and an MA from Brandeis University. Previously, he was a digital and spatial information specialist for archaeological and environmental projects in the United States and Turkey.

Francesco Mucio is a data consultant. The first time Francesco met the word data, it was just the plural of datum, and now he’s building a small consulting firm to help organizations to avoid or solve some of the problems he’s seen in the past. He likes to draw data models and optimize queries. He spends his free time with his daughter, who, for some reason, speaks four languages.

Manu Mukerji is senior director of data, machine learning, and analytics at 8×8. Manu’s background lies in cloud computing and big data, working on systems handling billions of transactions per day in real time. He enjoys building and architecting scalable, highly available data solutions and has extensive experience working in online advertising and social media.

Jacques Nadeau is the cofounder and CTO of Dremio. Previously, he ran MapR’s distributed systems team; was CTO and cofounder of YapMap, an enterprise search startup; and held engineering leadership roles at Quigo, Offermatica, and aQuantive. Jacques is cocreator and PMC chair of Apache Arrow, a PMC member of Apache Calcite, a mentor for Apache Heron, and the founding PMC chair of the open source Apache Drill project.

Syed Nasar is a solutions architect at Cloudera. As a big data and machine learning professional, his expertise extends to artificial intelligence, machine learning, and computer vision, and he has worked with a number of enterprises in bridging big data technologies with advanced statistical analysis, machine learning, and deep learning to create high-quality data products and intelligent systems that drive strategy and investment decisions. Syed is a founder of the Nashville Artificial Intelligence Society. His research interests include NLP, deep learning (mainly RNN and GAN), distributed systems, machine learning at scale, and emerging technologies. He is the founder of Nashville Artificial Intelligence Society. He holds a master’s degree in interactive intelligence from the Georgia Institute of Technology.

Paco Nathan is known as a “player/coach” with core expertise in data science, natural language processing, machine learning, and cloud computing. He has 35+ years of experience in the tech industry, at companies ranging from Bell Labs to early-stage startups. His recent roles include director of the Learning Group at O’Reilly and director of community evangelism at Databricks and Apache Spark. Paco is the cochair of Rev conference and an advisor for Amplify Partners, Deep Learning Analytics, Recognai, and Primer. He was named one of the "top 30 people in big data and analytics" in 2015 by Innovation Enterprise.

Alexander Ng is a director of infrastructure and DevOps at Manifold. Previously, he had a stint as an engineer and technical lead doing DevOps at Kyruus and engineering work for the Navy. He holds a BS in electrical engineering from Boston University.

Dinesh Nirmal is vice president of development for data and AI at IBM. His mission is to empower every organization to transform their industry—whether it’s aerospace, finance, or healthcare—by unlocking the power of their data. Dinesh speaks and writes internationally on operationalizing machine learning and advises business leaders on strategies to ready their enterprises for new technologies. He leads more than a dozen IBM Development Labs globally; recognizing a market need for data science mastery, he launched six machine learning hubs to work face-to-face with clients. Products in his portfolio regularly win major design awards, including two Red Dot Awards and the iF Design Award. Dinesh is a member of the board of the R Consortium and an advisor to Accel.AI. He lives in San Jose with his wife Catherine Plaia, formerly an engineer at Apple, and their two young sons.

Kyungtaak Noh runs the Metatron project team within product development at SK Telecom, South Korea’s largest wireless communications provider, where he’s responsible for managing product development for product and visualizing and coordinating with big data applications. He has 10+ years of experience working on applied big data platforms for for groupware, semiconductor, finance, and telecommunication as a software engineer.

Amy O’Connor is a big data evangelist and telecommunications specialist at Cloudera, the leading big data vendor. She advises customers globally as they introduce big data solutions and adopt enterprise-wide big data delivery capabilities. Amy was recently named one of Information Management’s 10 Big Data Experts to Know. Prior to joining Cloudera, Amy built and ran Nokia’s big data team, developing and managing Nokia’s data assets and leading a team of data scientists to drive insights. Previously, Amy was vice president of services marketing and also led strategy for the software and storage business units of Sun Microsystems.

Tim O’Reilly is the founder and CEO of O’Reilly Media, Inc. His original business plan was simply “interesting work for interesting people,” and that’s worked out pretty well. O’Reilly Media delivers online learning, publishes books, runs conferences, urges companies to create more value than they capture, and tries to change the world by spreading and amplifying the knowledge of innovators. Tim has a history of convening conversations that reshape the computer industry. In 1998, he organized the meeting where the term “open source software” was agreed on and helped the business world understand its importance. In 2004, with the Web 2.0 Summit, he defined how “Web 2.0” represented not only the resurgence of the web after the dot-com bust but a new model for the computer industry based on big data, collective intelligence, and the internet as a platform. In 2009, with his Gov 2.0 Summit, he framed a conversation about the modernization of government technology that has shaped policy and spawned initiatives at the federal, state, and local level and around the world. He has now turned his attention to implications of AI, the on-demand economy, and other technologies that are transforming the nature of work and the future shape of the business world. This is the subject of his book from Harper Business, WTF: What’s the Future and Why It’s Up to Us. In addition to his role at O’Reilly Media, Tim is a partner at early-stage venture firm O’Reilly AlphaTech Ventures (OATV) and serves on the boards of Maker Media (which was spun out from O’Reilly Media in 2012), Code for America, PeerJ, Civis Analytics, and PopVox.

Mike Olson cofounded Cloudera in 2008 and served as its CEO until 2013, when he took on his current role of chief strategy officer. As CSO, Mike is responsible for Cloudera’s product strategy, open source leadership, engineering alignment, and direct engagement with customers. Previously, Mike was CEO of Sleepycat Software, makers of Berkeley DB, the open source embedded database engine, and he spent two years at Oracle Corporation as vice president for embedded technologies after Oracle’s acquisition of Sleepycat. Prior to joining Sleepycat, Mike held technical and business positions at database vendors Britton Lee, Illustra Information Technologies, and Informix Software. Mike holds a bachelor’s and a master’s degree in computer science from the University of California, Berkeley.

Diego Oppenheimer is the founder and CEO of Algorithmia. An entrepreneur and product developer with extensive background in all things data, Diego has designed, managed, and shipped some of Microsoft’s most used data analysis products, including Excel, Power Pivot, SQL Server, and Power BI. Diego holds a bachelor’s degree in information systems and a master’s degree in business intelligence and data analytics from Carnegie Mellon University.

Richard Ott obtained his PhD in particle physics from the Massachusetts Institute of Technology, followed by postdoctoral research at the University of California, Davis. He then decided to work in industry, taking a role as a data scientist and software engineer at Verizon for two years. When the opportunity to combine his interest in data with his love of teaching arose at The Data Incubator, he joined and has been teaching there ever since.

M Pacer is a Jupyter core developer and a senior notebook engineer at Netflix. Previously, M was a postdoctoral researcher the Berkeley Institute for Data Science (BIDS), focusing on the intersection between Jupyter and scientific publishing. M holds a PhD from UC Berkeley, where their research used machine learning and human experiments to study casual explanation and causal inference, and a BS from Yale University, where their research focused on the role of causal language in evaluating scientific claims.

Yogesh Pandit is a senior software engineer in the Analytics Group at Roche. Currently, he’s leading the NLP efforts to support the company’s NAVIFY platform, which aims to support oncology care teams to review, discuss, and align on treatment decisions for the patient. Yogesh is a bioinformatician turned data engineer with experience in biomedical NLP. For the past few years, he’s been working on building data applications in the life sciences and healthcare space.

Marc Paradis vice president and dean of Data Science University (DSU) at UnitedHealth Group, where he has built out DSU to train the next generation of UnitedHealth Group’s data science and machine learning experts in the tools, techniques, and technologies of the discipline as well as in the architecture, content, and ontology of UnitedHealth Group’s uniquely integrated claims, clinical, and pharmacy data assets. Marc’s career has spanned a variety of healthcare companies in data-related roles, where he continuously seeks the unlock the hidden drivers of profit, efficiency, and value by applying the rigor and discipline of the scientific method to business datasets. He holds an SM from Massachusetts Institute of Technology in brain and cognitive sciences.

Vivek Pasari is a senior data engineer at Netflix, where he focuses on building high-quality data assets that drive innovation in delivering highly performant, consistent, and reliable user experiences for Netflix members. Previously, he spent several years in financial technology helping build large-scale cloud and data solutions.

Priyank Patel is the cofounder and chief product officer at Arcadia Data, where he leads the team’s charter in building visually beautiful and highly scalable analytical products and guides customers through their successful adoption. Previously, Priyank was part of the founding engineering team at Aster Data, where he designed core components of the Aster Database. He holds a master’s degree in computer science from Stanford University.

Joshua Patterson is a director of AI infrastructure at NVIDIA leading engineering for RAPIDS.AI. Previously, Josh was a White House Presidential Innovation Fellow and worked with leading experts across public sector, private sector, and academia to build a next-generation cyberdefense platform. His current passions are graph analytics, machine learning, and large-scale system design. Josh loves storytelling with data and creating interactive data visualizations. He holds a BA in economics from the University of North Carolina at Chapel Hill and an MA in economics from the University of South Carolina Moore School of Business.

Ji Peng is a problem solver who has developed the data backbone of Earnin, a high-growth financial company that allows anyone with a job and a bank account to get paid the minute they leave work. He has built machine learning systems that have given payroll flexibility to employees from more than 50,000 employers, guiding his data science team as they create sophisticated models to better understand the Earnin community. Ji holds a PhD from the University of Colorado, Boulder, and a BS from the University of Science and Technology of China (USTC).

Thomas Phelan is cofounder and chief architect of BlueData. Previously, a member of the original team at Silicon Graphics that designed and implemented XFS, the first commercially availably 64-bit file system; and an early employee at VMware, a senior staff engineer and a key member of the ESX storage architecture team where he designed and developed the ESX storage I/O load-balancing subsystem and modular pluggable storage architecture as well as led teams working on many key storage initiatives such as the cloud storage gateway and vFlash.

Carole Piovesan is a partner and cofounder at INQ Data Law, where she focuses on data governance, privacy law, cybersecurity, and artificial intelligence. Previously, Carole was a lawyer at a large Canadian law firm, where she served as colead of the firm’s National Cybersecurity, Privacy, and Data Management Group and a lead on artificial intelligence. Carole advises the Canadian government on legal and policy issues related to data and AI and regularly advises companies on issues related to their collection, storage, and use of data. Carole is a recognized expert on legal and policy issues relating to data and AI and is a frequent speaker and author on these topics.

Josh Poduska is the chief data scientist at Domino Data Lab. He has 17 years of experience in analytics. His work experience includes leading the statistical practice at one of Intel’s largest manufacturing sites, working on smarter cities data science projects with IBM, and leading data science teams and strategy with several big data software companies. Josh holds a master’s degree in applied statistics from Cornell University.

Gungor Polatkan is a machine learning expert and engineering leader with experience in building massive-scale distributed data pipelines serving personalized content at LinkedIn and Twitter. Most recently, he led the design and implementation of the AI backend for LinkedIn Learning and ramped up the recommendation engine from scratch to hyperpersonalized models learning billions of coefficients for 500M+ users. He deployed some of the first deep ranking models for search verticals at LinkedIn improving talent search. He enjoys leading teams, mentoring engineers, and fostering a culture of technical rigor and craftsmanship while iterating fast. Previously, he worked in several notable applied research groups at Twitter, Princeton, Google, MERL, and UC Berkeley. He has published and refereed papers at top-tier ML and AI venues, such as UAI, ICML, and PAMI.

Fait Poms is a CS PhD student at Stanford, where she is advised by Kayvon Fatahalian, as well as a research contractor for Oculus/Facebook. Fait’s PhD research focuses on designing algorithms and programmable systems for efficiently analyzing video. She has published and presented work at SIGGRAPH and CVPR on systems for large-scale video analysis and efficient 3D reconstruction using deep learning.

Cat Posey is a senior tech director on the leadership team in the Center for Machine Learning at Capital One, which focuses on research and strategic innovation initiatives in AI and ML, including the development of tools, technologies, frameworks, and partnerships with industry and academia. Cat is passionate about finding ways to shift the current dynamics within tech culture so the community can truly be a microcosm of the world and a place where all of its members can thrive. She’s also focused on developing and implementing AI and ML systems responsibly and in ways that put humanity at the forefront. Cat founded the Tech By Superwomen movement to shift the conversation to what works and what matters when it comes to creating a more inclusive tech industry. Previously, she was the head of strategic partnerships and alliances for the United States Digital Service, a tech startup founded by President Obama to change the technology infrastructure in order to better serve citizens. Cat is a recognized authority on issues impacting women in technology and an international speaker who has been featured in various national media publications.

Greg Quist is the cofounder, president, and CEO of SmartCover Systems, where he leads the strategic direction and operations of the company. Greg is a longtime member of the water community. He was elected to the Rincon del Diablo MWD board of directors in 1990 and for the past 27 years has served in various roles, including president and treasurer. Rincon’s Board appointed Greg to the San Diego County Water Authority Board in 1996, where he served for 12 years, leading a coalition of seven agencies to achieve more than $1M/year in water delivery savings. He is currently the chairman of the Urban Water Institute. With a background in the areas of metamaterials, numerical analysis, signal processing, pattern recognition, wireless communications, and system integration, Greg has worked as a technologist, manager, and executive at Alcoa, McDonnell-Douglas, and SAIC and has founded and successfully spun off several high-tech startups, primarily in real-time detection and water technology. He has held top-level government clearances and holds 14 patents and has several pending. Greg has an undergraduate degree in astrophysics with a minor in economics from Yale, where he played football and baseball, and a PhD in physics from the University of California, Santa Barbara. He currently resides in Escondido, CA. In his rare free time, he enjoys fly fishing, hiking, golf, basketball, and tennis.

Mohammad Quraishi is a senior principal technologist within the Data and Analytics Organization at Cigna, where he’s the lead engineer in the Big Data Guild; his primary focus is on Hadoop and streaming architectures. Mohammad has worked in the healthcare industry for 23 years. He holds a BS in computer science and engineering from the University of Connecticut at Storrs.

Irina Raicu is the director of the Internet Ethics Program at the Markkula Center for Applied Ethics at Santa Clara University. Previously, she was an attorney in private practice. Her work addresses a wide variety of issues, ranging from online privacy to net neutrality, from data ethics to social media’s impact on friendship and family, from the digital divide to the ethics of encryption, and from the ethics of artificial intelligence to the right to be forgotten. Her writing has appeared in a variety of publications, including the Atlantic, USA Today, MarketWatch, Slate, HuffPost, the San Jose Mercury News, the San Francisco Chronicle, and Recode. She’s a Certified Information Privacy Professional (US) and is a member of the Partnership on AI’s Working Group on Fair, Transparent, and Accountable AI. In collaboration with the staff of the High Tech Law Institute, Irina manages the ongoing IT, Ethics, and Law lecture series, which has brought to campus speakers such as journalist Julia Angwin, ethicists Luciano Floridi and Patrick Lin, and then-FTC commissioner Julie Brill. She holds a JD from Santa Clara University’s School of Law, a master’s degree in English and American literature from San Jose State University, and a bachelor’s degree in English from UC Berkeley. She tweets at @IEthics and is the primary contributor to the blog Internet Ethics: Views from Silicon Valley. As a teenager, Irina came to the US with her family as a refugee; her background informs her interest in the internet as a tool whose use has profound ethical implications worldwide.

Ashwin Ramachandran is the Senior product manager for Syncsort’s data integration portfolio, Syncsort Connect. In his five and a half years at Syncsort, he has had the opportunity to engage with customers at multiple levels, understanding the challenges organizations face embracing next wave technologies. Across all of these instances, he has particularly enjoyed the process of creating new ways in which Syncsort software can help customers overcome their pressing business challenges.

Karthik Ramasamy is the cofounder of Streamlio, a company building next-generation real-time processing engines. Karthik has more than two decades of experience working in parallel databases, big data infrastructure, and networking. Previously, he was engineering manager and technical lead for real-time analytics at Twitter, where he was the cocreator of Heron; cofounded Locomatix, a company that specialized in real-time stream processing on Hadoop and Cassandra using SQL (acquired by Twitter); worked briefly on parallel query scheduling at Greenplum (acquired by EMC for more than $300M); and designed and delivered platforms, protocols, databases, and high-availability solutions for network routers at Juniper. He’s the author of several patents, publications, and one best-selling book, Network Routing: Algorithms, Protocols, and Architectures. Karthik holds a PhD in computer science from the University of Wisconsin–Madison with a focus on databases, where he worked extensively in parallel database systems, query processing, scale-out technologies, storage engines, and online analytical systems. Several of these research projects were spun out as a company later acquired by Teradata.

Sushant Rao is a cloud product marketer at Cloudera.

Nancy Rausch is a senior manager at SAS. Nancy has been involved for many years in the design and development of SAS’s data warehouse and data management products, working closely with customers and authoring a number of papers on SAS data management products and best practice design principals for data management solutions. She holds an MS in computer engineering from Duke University, where she specialized in statistical signal processing, and a BS in electrical engineering from Michigan Technological University. She has recently returned to college and is pursuing an MS in analytics from Capella University.

Joseph Regensburger leads the Research Group at Immuta, where he focuses on model risk management and privacy-preserving machine learning. Previously, he was chief scientist at Illumination Works, LLC and principal research scientist at the Battelle Memorial Institute. Joseph has led research efforts characterizing airport security screening devices, engineering image analysis software, and developing machine learning algorithms for biological detection. He received both Battelle’s Technical Achievement Award and Illumination Works’s Innovation Award. He holds a PhD in physics from the Ohio State University, where his research focused on experimental high-energy physics—specifically the detection of rare decays of D0 mesons.

Jen Ren is a program manager at Microsoft, focused on creating data wrangling tools for AI datasets. She studied health policy and computer science at Stanford University, where she was also part of the Data Challenge Lab.

Luciano Resende is a senior technical staff manager (STSM) and open source data science and AI platform architect at IBM CODAIT (formerly Spark Technology Center). He’s a member of ASF, where he’s been contributing to open source for over 10 years. He contributes to various big data-related Apache projects around the Apache Spark ecosystem as well as Jupyter ecosystem projects, building a scalable, secure, and flexible enterprise data science platform.

Bartley Richardson is a senior data scientist on the AI infrastructure team at NVIDIA. Bartley’s focus at NVIDIA is the research and application of GPU-accelerated methods that can help solve today’s information security and cybersecurity challenges. Previously, Bartley was a technical lead and performer on multiple DARPA research projects, where he applied data science and machine learning algorithms at scale to solve large cybersecurity problems. He was also the principal investigator of an internet of things research project focused on applying machine and deep learning techniques to large amounts of IoT data to provide intelligence value relating to form, function, and pattern of life. His primary research areas involve NLP and sequence-based methods applied to cyber network datasets as well as cross-domain applications of machine and deep learning solutions to tackle the growing number of cybersecurity threats. He loves using data and visualizations to tell stories and help make complex concepts more relatable. Bartley holds a PhD in computer science and engineering from the University of Cincinnati with a focus on loosely and unstructured query optimization and a BS in computer engineering with a focus on software design and AI.

Brian is Rieger is cofounder and COO of Labelbox, the industry-leading training data software that is accelerating global access to artificial intelligence. An accomplished aerospace engineer, data scientist, and software developer turned serial entrepreneur, Brian began his career doing aerodynamics, testing, and flight certification of the Boeing 787 Dreamliner. He then built an aerospace company that put hardware on the International Space Station. Brian was recognized as one of Forbes’s “30 under 30” for transforming enterprise technology with machine intelligence.

Kelley Rivoire is the head of data infrastructure at Stripe, where she leads the Data Infrastructure Group. As an engineer, she built Stripe’s first real-time machine learning evaluation of user risk. Previously, she worked on nanophotonics and 3D imaging as a researcher at HP Labs. She holds a PhD from Stanford.

David Rodriguez is a senior research engineer at Cisco Umbrella (formerly OpenDNS). He has coauthored multiple pending patents with Cisco in distributed machine learning applications centered around deep learning and behavioral analytics. He’s a frequent speaker about machine learning in cybersecurity at conferences including Flink Forward, Black Hat, Flocon, Virus Bulletin, and HitBSEC. David holds an MA in mathematics from San Francisco State University.

Pierre Romera is the chief technology officer at the International Consortium of Investigative Journalists (ICIJ), where he manages a team of programmers working on the platforms that enabled more than 300 journalists to collaborate on the Paradise Papers and Panama Papers investigations. Previously, he cofounded Journalism++, the Franco-German data journalism agency behind the Migrant Files, a project that won the European Press Prize in 2015 for Innovation. He is one of the pioneers of data journalism in France.

Alfred Rossi is a theoretical computer scientist and research scientist at Immuta, where his efforts are currently focused on differential privacy and model risk management. His research interests include clustering (especially in alternative settings) and privacy. Alfred holds a PhD in computer science and an MS in physics, both from the Ohio State University.

Nikki Rouda is a principal product marketing manager at Amazon Web Services (AWS). Nikki has decades of experience leading enterprise big data, analytics, and data center infrastructure initiatives. Previously, he held senior positions at Cloudera, Enterprise Strategy Group (ESG), Riverbed, NetApp, Veritas, and UK-based Alertme.com (an early consumer IoT startup). Nikki holds an MBA from Cambridge’s Judge Business School and an ScB in geophysics from Brown University.

Craig Rowley is a data solutions architect and scientist at Columbia Sportswear. Craig seeks to inform the art of business through data and science, sifting through petabytes of information to find the “little data”—those nuggets of information and insight—that help deliver the right products and experiences to the right consumers at the right time…and more importantly, to do the right thing for consumers by protecting their right to privacy on a global, comprehensive, and even predictive scale. Luck and great opportunities have helped him deliver patents on streaming behavioral data models, adaptive augmented reality applications, location-aware engagement intelligence, in-the-moment predictive algorithms for wearable devices, fraud detection and prediction platforms, and personalized, connection-based recommenders. His specialities include petabyte-scale dataflow execution architectures to enable full-loop data science, data exploration and modeling of semistructured, unstructured, and structured data, inventing new machine learning algorithms, heuristics, and applications. His interests include science fiction movies and books, video games, and learning.

John Rutherford builds machine learning applications and helps develop the Wise data science platform at GE. Previously, he was the data scientist for an energy efficiency startup, where he headed algorithm development and exploratory analyses. He holds physics, mathematics, and astrophysics degrees from Stanford and MIT.

Iman Saleh is a research scientist with the Automotive Solutions Group at Intel. Iman has authored 30+ technical publications in the areas of big data, formal data specification, service-oriented computing, and privacy-preserving data mining. Her research interests include ethical AI, machine learning, privacy-preserving solutions, software engineering, data modeling, web services, formal methods, and cryptography. She holds a PhD from the Computer Science Department at Virginia Tech, a master’s degree in computer science from Alexandria University, Egypt, and a master’s degree in software engineering from Virginia Tech.

David E. Sanger is the national security correspondent for the New York Times as well as a national security and political contributor for CNN and a frequent guest on CBS This Morning, Face the Nation, and many PBS shows. David’s years as a foreign correspondent have given him a unique view into the rise of Asia, nuclear proliferation, global competition, and a volatile Middle East. A three-time Pulitzer Prize winner, including as a member of the 2017 Pulitzer Prize-winning team in international reporting, he is one of the nation’s most lucid analysts of geopolitics, globalization, and cyberpower. He’s the author of national best-sellers Confront and Conceal: Obama’s Secret Wars and Surprising Use of American Power, a riveting analysis of the Obama administration’s foreign policy, including its covert reliance on cyberwarfare, drones, and special operations forces that Foreign Affairs called an “astonishingly revealing insider’s account,” and The Inheritance: The World Obama Confronts and the Challenges to American Power, an in-depth examination of American foreign policy successes and failures. His new book, The Perfect Weapon: War, Sabotage, and Fear in the Cyber Age, offers an incisive look into how cyberwarfare is influencing elections, threatening national security, and bringing us to the brink of global war.

A 30-year veteran of the New York Times, Sanger’s coverage of the Iraq and Korea crises took home the Weintal Prize, one of the highest honors for diplomatic reporting. He also won the White House Correspondents’ Association Aldo Beckman prize for his presidential coverage.
Early in his career, Sanger covered technology and economics, before turning to foreign policy. Over the years, he has focused on North Korea’s nuclear weapons program, the rise and fall of Japan, and China’s increasing power and influence. Later, he covered domestic and foreign policy issues as the Times’s White House correspondent from 1999 to 2006. He’s a featured journalist in Alex Gibney’s 2016 docu-thriller Zero Days, based largely on his own investigation of the secret American and Israeli cyberprogram to attack Iran’s nuclear facilities. David teaches national security policy as a visiting scholar and adjunct professor at Harvard University’s Kennedy School of Government.

Akshai Sarma is a principal software engineer working in big data, ETL, analytics, and distributed computing at Yahoo. He enjoys dealing with problems at scale, decreasing latency, improving quality, and creating systems that handle billions of events and terabytes of data—both streaming and batch.

Osman Sarood leads the infrastructure team at Mist Systems, where he helps Mist scale the Mist Cloud in a cost-effective and reliable manner. Osman has published more than 20 research papers in highly rated journals, conferences, and workshops and has presented his research at several academic conferences. He has over 400 citations along with an i10-index and h-index of 12. Previously, he was a software engineer at Yelp, where he prototyped, architected, and implemented several key production systems and architected and authored Yelp’s autoscaled spot infrastructure, fleet_miser. Osman holds a PhD in high-performance computing from the University of Illinois Urbana-Champaign, where he focused on load balancing and fault tolerance.

Jörg Schad is Head of Machine Learning at ArangoDB. In a previous life, he has worked on or built machine learning pipelines in healthcare, distributed systems at Mesosphere, and in-memory databases. He received his Ph.D. for research around distributed databases and data analytics. He’s a frequent speaker at meetups, international conferences, and lecture halls.

Robert Schroll is a data scientist in residence at the Data Incubator. Previously, he held postdocs in Amherst, Massachusetts, and Santiago, Chile, where he realized that his favorite parts of his job were teaching and analyzing data. He made the switch to data science and has been at the Data Incubator since. Robert holds a PhD in physics from the University of Chicago.

Jonathan Seidman is a software engineer on the cloud team at Cloudera. Previously, he was a lead engineer on the big data team at Orbitz, helping to build out the Hadoop clusters supporting the data storage and analysis needs of one of the most heavily trafficked sites on the internet. Jonathan is a cofounder of the Chicago Hadoop User Group and the Chicago Big Data Meetup and a frequent speaker on Hadoop and big data at industry conferences such as Hadoop World, Strata, and OSCON. Jonathan is the coauthor of Hadoop Application Architectures from O’Reilly.

Mehul Shah heads two cloud services at AWS: AWS Lake Formation and AWS Glue. His expertise spans large-scale data management, distributed systems, and energy-efficient computing. His work has been published in top-tier conferences and journals and has won several awards including a Test of Time. Previously, he was cofounder and CEO of Amiato, a startup that offered a real-time ETL cloud service, and principal research scientist at HP Labs. He holds a PhD from UC Berkeley, where his work focused on adding fault tolerance and autoscaling in the TelegraphCQ stream processing system, and both an MEng and BS in CS and physics from MIT. He’s currently a member of the Sort Benchmark committee.

Gwen Shapira is a system architect at Confluent, where she helps customers achieve success with their Apache Kafka implementations. She has 15 years of experience working with code and customers to build scalable data architectures, integrating relational and big data technologies. Gwen currently specializes in building real-time reliable data processing pipelines using Apache Kafka. Gwen is an Oracle Ace Director, the coauthor of Hadoop Application Architectures, and a frequent presenter at industry conferences. She is also a committer on Apache Kafka and Apache Sqoop. When Gwen isn’t coding or building data pipelines, you can find her pedaling her bike, exploring the roads and trails of California and beyond.

Sonali Sharma a data engineer on the data personalization team at Netflix, which, among other things, delivers recommendations made for each user. The team is responsible for the data that goes into training and scoring of the various machine learning models that power the Netflix home page. They have been working on moving some of the company’s core datasets from being processed in a once-a-day daily batch ETL to being processed in near real time using Apache Flink. A UC Berkeley graduate, Sonali has worked on a variety of problems involving big data. Previously, she worked on the mail monetization and data insights engineering team at Yahoo, where she focused on building great data-driven products to do large-scale unstructured data extractions, recommendation systems, and audience insights for targeting using technologies like Spark, the Hadoop ecosystem (Pig, Hive, MapReduce), Solr, Druid, and Elasticsearch.

Vishakha Sharma is a data scientist for diagnostic information solutions at Roche, where she leads advanced analytics initiatives such as natural language processing (NLP) and machine learning (ML) to discover key insights improving NAVIFY product portfolio, leading to better and more efficient patient care. Vishakha has authored 40+ peer-reviewed publications and proceedings and has given 15+ invited talks. She serves on the program committee of the ACM-W, AMIA, and ACM-BCB. Her research work has been funded by the NIH Big Data to Knowledge (BD2K) initiative to build an NLP precision medicine software to automate molecular and clinical information extraction, categorization, and ranking of clinical evidence associated with biomarkers that predict response to cancer therapies. She holds a PhD in computer science.

Kimberly Shenk is the cofounder of NakedPoppy, an online beauty company that offers personalized clean makeup. Previously, she was the director of data science products at Domino Data Lab, the director of data science at Eventbrite, cofounder of a boutique data science consultancy, a marketing data scientist in retail, and a captain and data scientist in the United States Air Force and at Draper Labs. She serves on the board of the USF Data Science Institute. Kimberly holds an MS from MIT and a BS from the US Air Force Academy.

Aashish Sheshadri is a research engineer at PayPal, where he currently ideates and applies deep learning to new avenues and actively contributes to the Jupyter ecosystem and the SEIF Project. He holds an MS in computer science from the University of Texas at Austin, where his research focused on active learning with human-in-the-loop systems.

Daragh Sibley is director of data science at Stitch Fix, where he leads a team of data scientists that use algorithms and the scientific method to optimize the portfolio of products stocked in Stitch Fix’s inventory. Previously, Daragh spent a decade in academia, where he developed neural networks of human language acquisition and tested their predictions with behavioral and neuroimaging experiments.

Alkis Simitsis is a chief scientist for cybersecurity analytics at Micro Focus. Alkis has more than 15 years of experience building innovative information and data management solutions in areas like real-time business intelligence, security, massively parallel processing, systems optimization, data warehousing, graph processing, and web services. He holds 26 US patents and has filed over 50 patent applications in the US and worldwide. He’s published more than 100 papers in refereed international journals and conferences (top publications cited 5,000+ times) and frequently serves in various roles in program committees of top-tier international scientific conferences. He’s also an IEEE senior member and a member of the ACM.

Peter Warren Singer is strategist at New America and an editor at Popular Science magazine. He has been named by the Smithsonian as one of the nation’s 100 leading innovators, by Defense News as one of the 100 most influential people in defense issues, by Foreign Policy to their “top 100 global thinkers” list, as an official “mad scientist” for the US Army’s Training and Doctrine Command, and by Onalytica social media data analysis as one of the 10 most influential voices in the world on cybersecurity and the 25th most influential in the field of robotics. Peter’s award-winning books include Corporate Warriors: The Rise of the Privatized Military Industry, Children at War, Wired for War: The Robotics Revolution and Conflict in the 21st Century, Cybersecurity and Cyberwar: What Everyone Needs to Know, and Ghost Fleet: A Novel of the Next World War, a technothriller crossed with nonfiction research, which has been endorsed by people who range from the chairman of the Joint Chiefs to the coinventor of the internet to the writer of HBO’s Game of Thrones. His latest book is LikeWar, which explores how social media has changed war and politics and how war and politics has changed social media. It was named an Amazon book of the month and a New York Times “new and notable” selection. In its review, Booklist argued that “LikeWar should be required reading for everyone living in a democracy and all who aspire to.” Peter’s past work includes serving at the Office of the Secretary of Defense, Harvard University, and as the founding director of the Center for 21st Century Security and Intelligence at Brookings, where he was the youngest person named senior fellow in its 100-year history.

Animesh Singh is a senior technical staff member (STSM) and program director for the IBM Watson and Cloud Platform, where he leads machine learning and deep learning initiatives on IBM Cloud and works with communities and customers to design and implement deep learning, machine learning, and cloud computing frameworks. He has a proven track record of driving design and implementation of private and public cloud solutions from concept to production. Animesh has worked on cutting-edge projects for IBM enterprise customers in the telco, banking, and healthcare industries, particularly focusing on cloud and virtualization technologies, and led the design and development first IBM public cloud offering.

Harinder Singh is the global director of data strategy and solution architecture at AB inBev. Harinder is passionate about building data products to unlock the power of information within the organization. Previously, he led the data strategy and analytics program at Walmart.

Pramod Singh is a senior machine learning engineer at Walmart Labs. He has extensive hands-on experience in machine learning, deep learning, AI, data engineering, designing algorithms, and application development. He has spent more than 10 years working on multiple data projects at different organizations. He’s the author of three books Machine Learning with PySpark, Learn PySpark, and Learn TensorFlow 2.0. He’s also a regular speaker at major conferences such as the O’Reilly Strata Data and AI Conferences. Pramod holds a BTech in electrical engineering from BATU, and an MBA from Symbiosis University. He’s also done data science certification from IIM–Calcutta. He lives in Bangalore with his wife and three-year-old son. In his spare time, he enjoys playing guitar, coding, reading, and watching football.

Swatee Singh is the vice president of the big data platform and the first female distinguished architect of the machine learning platform at American Express, where she’s spearheading machine learning transformation. Swatee’s a proponent of democratizing machine learning by providing the right tools, capabilities, and talent structure to the broader engineering and data science community. The platform her team is building looks to leverage American Express’s closed loop data to enhance its customer experience by combining artificial intelligence, big data, and the cloud, incorporating guiding pillars such as ease of use, reusability, shareability, and discoverability. Swatee also led the American Express recommendation engine road map and delivery for card-linked merchant offers as well as for personalized merchant recommendations. Over the course of her career, she’s applied predictive modeling to a variety of problems ranging from financial services to retailers and even power companies. Previously, Swatee was a consultant at McKinsey & Company and PwC, where she supported leading businesses in retail, banking and financial services, insurance, and manufacturing, and cofounded a medical device startup that used a business card-sized thermoelectric cooling device implanted in the brain of someone with epilepsy as a mechanism to stop seizures. Swatee holds a PhD focused on machine learning techniques from Duke University.

Ram Shankar is a data cowboy on the Azure security data science team at Microsoft, where his team focuses on modeling massive amounts of security logs to surface malicious activity. His work has appeared in industry conferences like DEF CON, BSides, BlueHat, DerbyCon, MIRCon, Infiltrate, and Strata as well as academic conferences like NIPS and ACM-CCS. Ram holds a degree focused on machine learning and security from Carnegie Mellon University. He’s currently an affiliate at the Berkman Klein Center at Harvard, exploring the intersection of machine learning and security.

Guoqiong Song is a senior deep learning software engineer on the big data technology team at Intel. She’s interested in developing and optimizing distributed deep learning algorithms on Spark. She holds a PhD in atmospheric and oceanic sciences with a focus on numerical modeling and optimization from UCLA.

Guoqiong Song是英特尔大数据技术团队的高级深度学习软件工程师。 她拥有加州大学洛杉矶分校的大气和海洋科学博士学位，专业方向是数值建模和优化。 她现在的研究兴趣是开发和优化分布式深度学习算法。

Nathan Speidel develops novel solutions to big data problems at Yahoo (Verizon Media Group) and works on the Audience Data ETL pipeline. He enjoys leveraging ubiquitous open source tools such as Kafka, Storm, Spark, HDFS, Oozie, and Hive as well as new, cutting-edge open source tools like Bullet to push the limits of streaming data processing, visualization, querying, and transformation.

Paul Spiegelhalter is a data scientist and deep learning specialist at Pythian, where he’s recognized for his deep expertise in utilizing cutting-edge advances in artificial intelligence and machine learning in order to transform groundbreaking research into usable algorithms. Paul’s experience with predictive analytics and algorithmic modeling runs across a number of industries, including computer vision, predictive maintenance, online advertising and user analysis, medical diagnostics, natural language processing, and anomaly detection. He holds a PhD in mathematics from the University of Illinois at Urbana-Champaign.

AWS Solutions Architect

Ankit Srivastava is a senior data scientist on the core data science team for the Azure Cloud + AI Platform Division at Microsoft, where he focuses on commercial and education segment data science projects within the company. Previously, he was a developer on the data integration and insights team. He has built several production-scale ML enrichments that are leveraged for sales compensation and senior leadership team metrics.

Mac Steele is the director of product at Domino, where he leads strategic development of the company’s data science platform. Based in San Francisco, he works closely with leading financial services, insurance, and technology companies to build a mature data science process across their entire organization. He has extensive experience leading advanced analytical organizations in both finance and tech. Previously, Mac worked in the Research Group at Bridgewater Associates, the world’s largest hedge fund, where he developed quantitative models for the firm’s emerging market portfolio; he also built the core data capability at leading fintech company Funding Circle. Steele holds a degree (summa cum laude) from the Woodrow Wilson School of Public and International Affairs at Princeton University.

Wim Stoop is a senior product marketing manager at Cloudera.

Dave Stuart is a senior technical executive within the US Department of Defense, where he’s leading a large-scale effort to transform the workflows of thousands of enterprise business analysts through Jupyter and Python adoption, making tradecraft more efficient, sharable, and repeatable. Previously, Dave led multiple grassroots technology adoption efforts, developing innovative training methods that tangibly increased the technical proficiency of a large noncoding enterprise workforce.

Patrick Stuedi is a member of the research staff at IBM research Zurich. His research interests include distributed systems, networking, and operating systems. The general theme of his work is to explore how modern networking and storage hardware can be exploited in distributed systems. Previously, he was a postdoc at Microsoft Research Silicon Valley. Patrick is the creator of several open source projects such as DiSNI (RDMA for Java), DaRPC (Low latency RPC), and Apache Crail (incubating). He holds a PhD from ETH Zurich.

Jagane Sundar is the CTO at WANdisco. Jagane has extensive big data, cloud, virtualization, and networking experience. He joined WANdisco through its acquisition of AltoStor, a Hadoop-as-a-service platform company. Previously, Jagane was founder and CEO of AltoScale, a Hadoop- and HBase-as-a-platform company acquired by VertiCloud. His experience with Hadoop began as director of Hadoop performance and operability at Yahoo. Jagane’s accomplishments include creating Livebackup, an open source project for KVM VM backup, developing a user mode TCP stack for Precision I/O, developing the NFS and PPP clients and parts of the TCP stack for JavaOS for Sun Microsystems, and creating and selling a 32-bit VxD-based TCP stack for Windows 3.1 to NCD Corporation for inclusion in PC-Xware. Jagane is currently a member of the technical advisory board of VertiCloud. He holds a BE in electronics and communications engineering from Anna University.

Václav Surovec is a senior big data engineer and comanages the Big Data Department at Deutsche Telekom IT. The department’s more than 45 engineers deliver big data projects to Germany, the Netherlands, and the Czech Republic. Recently, he led the commercial roaming project. Previously, he worked at T-Mobile Czech Republic while he was still a student of Czech Technical University in Prague.

Elizabeth Svoboda is an award-winning journalist and contributor to MIT Technology Review, Aeon, Sapiens, Psychology Today, the Washington Post, and other publications. She is the author of What Makes a Hero? The Surprising Science of Selflessness as well as the children’s book The Life Heroic (forthcoming from Zest Books in 2019). She’s fascinated with the subtle forces that guide our decisions and actions, sometimes without our knowledge.

Ian Swanson is vice president of product for AI and machine learning at Oracle, where he oversees the product strategy for the company’s AI/ML PaaS offerings. Previously, Ian was founder and CEO of DataScience.com (acquired by Oracle in 2018)—a company that provided an industry-leading enterprise data science platform that combined the tools, libraries, and languages data scientists loved with the infrastructure and workflows their organizations needed. Earlier in his career, he was an executive at American Express and Sprint and CEO of Sometrics, a company that launched the industry’s first global virtual currency platform (acquired by American Express in 2011). That platform, for which he earned a patent, managed more than 3.3 trillion units of virtual currency and served an online audience of 250 million in more than 180 countries. A sought-after speaker and expert on digital transformation, data science, big data, and performance-based analytics, Ian actively advises Fortune 500 companies and invests in leading startups.

Shubham Tagra is a senior staff engineer at Qubole, working on Presto and Hive development and making these solutions cloud ready. Previously, Shubham worked on the storage area network at NetApp. Shubham holds a bachelor’s degree in computer engineering from the National Institute of Technology, Karnataka, India.

David Talby is a chief technology officer at Pacific AI, helping fast-growing companies apply big data and data science techniques to solve real-world problems in healthcare, life science, and related fields. David has extensive experience in building and operating web-scale data science and business platforms, as well as building world-class, agile, distributed teams. Previously, he led business operations for Bing Shopping in the US and Europe with Microsoft’s Bing Group and built and ran distributed teams that helped scale Amazon’s financial systems with Amazon in both Seattle and the UK. David holds a PhD in computer science and master’s degrees in both computer science and business administration.

Haodong Tang is a big data storage optimization and development engineer at Intel.

Subhadra Tatavarti leads strategy and product for data platforms and infrastructure at PayPal. Her team manages and propels the data platforms that power PayPal’s core customers, processing over 250 PB of data, and builds products that cater to over 5,000 PayPal developers, analysts, and data scientists—with the goal to not just enable this community but also drive efficiency, reduce friction, and reduce time to market, which in turn drives PayPal’s growth. Subhadra is an experienced leader of large organization-wide transformations that drive innovation and accelerate business delivery.

James Taylor is a software engineer in the Data Infrastructure Group at Lyft, where he works on big data systems. Previously, he was an architect at Salesforce, where he founded the Apache Phoenix project and led its development, and worked on federated query processing systems and event-driven programming platforms at BEA Systems.

Serban Teodorescu is an SRE at Adobe, where he’s part of a small team that manages 20+ Cassandra clusters for Adobe Audience Manager. Previously, he was a Python programmer, and he’s still trying to find out how a developer who preferred SQL databases ended up as an SRE for a Cassandra team. Apart from Cassandra and Python, he’s interested in automating infrastructure provisioning with Terraform.

Rhonda Textor is the head of data science at True Fit, a platform dedicated to helping shoppers find clothes and shoes they love and keep. Rhonda is passionate about modeling fit and style elements of both shoppers and garments in order to recommend products to shoppers that they love and that fit and flatter. Previously, Rhonda applied machine learning and data science to problems in remote sensing such as land cover classification of satellite images and problems in national security, such as detecting threats in imagery.

Yves Thibaudeau is a mathematical statistician and principal researcher at the US Census Bureau. His publications include a book chapter on record linkage and computer matching in the Annals of Applied Statistics. He’s given a number of presentations on statistics and record linkage at conferences since 1988. Yves holds a PhD and an MS in statistics from Carnegie Mellon and a BSc in mathematics from McGill.

Alex Thomas is a data scientist at John Snow Labs. He’s used natural language processing (NLP) and machine learning with clinical data, identity data, and job data. He’s worked with Apache Spark since version 0.9 as well as with NLP libraries and frameworks including UIMA and OpenNLP.

Rachel Thomas was selected by Forbes as one of “20 Incredible Women in AI”, was an early engineer at Uber, and earned her math PhD at Duke. She is co-founder of fast.ai, which created the “Practical Deep Learning for Coders” course that over 200,000 students have taken, and she is also a professor at the University of San Francisco Data Institute. Rachel is a popular writer and keynote speaker on the topics of data science ethics, bias, machine learning, and technical education. Her writing has been read by nearly a million people and has made the front page of Hacker News 9×.

Skyler Thomas is an engineer at MapR, where he is designing Kubernetes-based infrastructure to deliver machine learning and big data applications at scale. Previously, Skyler was chief architect for WebSphere user experience at IBM, where he worked with more than a hundred customers to deliver extreme-scaled applications in the healthcare, financial services, and retail industries.

Jordan Tigani was one of the founding engineers on Google BigQuery, wrote the first book on the subject, and now leads its vision and roadmap as director of product management. Previously, Jordan worked at Microsoft Research and on the Windows Kernel team as well as at a number of star-crossed startups. He holds a bachelor’s degree from Harvard and a master’s degree from the University of Washington.

Steve Touw is the cofounder and CTO of Immuta. Steve has a long history of designing large-scale geotemporal analytics across the US intelligence community, including some of the very first Hadoop analytics, as well as frameworks to manage complex multitenant data policy controls. He and his cofounders at Immuta drew on this real-world experience to build a software product to make data security and privacy controls easier. Previously, Steve was the CTO of 42six (acquired by Computer Sciences Corporation), where he led a large big data services engineering team. Steve holds a BS in geography from the University of Maryland.

Martin Traverso is a cofounder of the Presto Software Foundation and one of the original creators of Presto. Previously, he was a software engineer at Facebook, where he lead the Presto development team.

Cindy Tseng is a research scientist with the Applied Research in Automotive Driving Group at Intel, where she has recently been focusing on bias detection in convolution neural nets. Cindy has also worked in the high-throughput computing and deep learning hardware accelerator spaces. She holds a master’s degree from the Electrical and Computer Engineering Department at Carnegie Mellon University and a bachelor’s degree in electrical engineering and computer science from the University of Michigan-Ann Arbor. Cindy is currently enrolled as a part-time student in the Masters in Data Science Program in Computer Science at the University of Illinois Urbana-Champaign.

Geoff Tudor is vice president and general manager at Vizion.ai. Geoff has over 22 years of experience in storage, broadband, and networking. Previously, he was chief cloud strategist at Hewlett Packard Enterprise, where he led CxO engagements for Fortune 100 private cloud opportunities, resulting in 10X growth to over $1B in revenues while positioning HPE as the #1 private cloud infrastructure supplier globally. Before that, he was cofounder and launched award-winning products in cloud storage at Nirvanix (acquired by Oracle), backup and recovery at GNS (acquired by Symantec), and gigabit ethernet last-mile networking with Advent Networks and Tellaire (acquired by MRV Communications). He was nominated for the Ernst and Young Entrepreneur of the Year award and recognized by Discover magazine as an Innovator. Geoff holds an MBA from the University of Texas at Austin and a BA from Tulane University. He holds patents in satellite communications. He resides in Austin, TX, with his wife and two children.

Sandeep Uttamchandani is the hands-on chief data architect and head of data platform engineering at Intuit, where he’s leading the cloud transformation of the big data analytics, ML, and transactional platform used by 3M+ small business users for financial accounting, payroll, and billions of dollars in daily payments. Previously, Sandeep held engineering roles at VMware and IBM and founded a startup focused on ML for managing enterprise systems. Sandeep’s experience uniquely combines building enterprise data products and operational expertise in managing petabyte-scale data and analytics platforms in production for IBM’s federal and Fortune 100 customers. Sandeep has received several excellence awards. He has over 40 issued patents and 25 publications in key systems conference such as VLDB, SIGMOD, CIDR, and USENIX. Sandeep is a regular speaker at academic institutions and conducts conference tutorials for data engineers and scientists. He advises PhD students and startups, serves as program committee member for systems and data conferences, and was an associate editor for ACM Transactions on Storage. He blogs on LinkedIn and his personal blog, Wrong Data Fabric. Sandeep holds a PhD in computer science from the University of Illinois at Urbana-Champaign.

Vinod Vaikuntanathan is an associate professor of computer science within MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and a cofounder of Duality Technologies. His research focuses on lattice-based cryptography and the theory and practice of computing on encrypted data. Vinod holds a PhD in computer science from MIT, where he received the George M. Sprowls Award for the best computer science thesis. His teaching and research in cybersecurity was recently recognized with MIT’s Harold E. Edgerton Faculty Achievement Award, a Sloan Faculty Fellowship, a Microsoft Faculty Fellowship, and a DARPA Young Faculty Award.

Nick Vandivere is CEO at ThoughtTrace, where he has led the company’s transformation into a technology and thought leader for the application of applied artificial intelligence and machine learning. He believes that product innovation, reliability, and an outstanding user experience are the required ingredients for exceptional performance and long-term value. Previously, he was an officer in the US Army and served in an advisory role with the US Department of State. Nick holds a BS in economics from Texas A&M University.

Stefaan Vervaet is a San Jose-based storage expert and senior director of product marketing and strategic alliances for Western Digital’s Data Center Systems business unit, where he’s responsible for leading marketing and business development efforts to deliver advanced object storage-based systems and emerging storage solutions for today’s at-scale enterprise and cloud workloads, including big data analytics, virtualization, application acceleration, and long-term backup/active archives. He has 15 years of experience as a business-focused technologist in the data storage and backup industry, with an extensive startup background that includes product management and go-to-market positions in the backup space and technical sales and support. An innovator with a proven track record, Stefaan successfully helped build startup companies like DataCenter Technologies, a dedupe technology (acquired by Veritas), and Amplidata, a leading object storage vendor (acquired by HGST, a Western Digital Company), where he established and built the US office running technical sales, support, and operations worldwide. He holds a master’s degree in applied informatics from the University of Ghent, Belgium.

Nancy Vitale is the CHRO and senior vice president of human resources for Genentech as well as a member of the Genentech Executive Committee. She’s responsible for leading the HR team that’s dedicated to creating a great place for the organization’s 14,000 employees to do their best work in pursuit of the company’s important mission. Nancy is also a board member for the Make-A-Wish Foundation of America, another mission-driven organization. Previously, Nancy was director of HR for the Gillette North American Commercial Division at Procter & Gamble (P&G), where she was integrally involved in the merger of Gillette and P&G; was vice president of HR for CIGNA’s Group Insurance Division; and held other senior HR positions in a variety of industries and companies, including Deloitte Consulting, DANKA Office Imaging, and the Times Publishing Company. Nancy is known for her drive and leadership. She thrives on challenges, particularly those that involve complex organizational dynamics. Her life purpose is to “make meaningful connections,” which she explains as being for both people and ideas. Nancy holds a bachelor’s degree in business administration from the University of Michigan and an MBA from Emory University. In 2015, Nancy was recognized by the San Francisco Business Times as one of the “most influential women in the Bay Area” and in 2016 was named to its “forever influential” honor roll.

Lars Volker is a software engineer at Cloudera. He has worked on various parts of Apache Impala, including crash handling, its Parquet scanners, and scan range scheduling. Most recently, he worked on integrating Kudu’s RPC framework into Impala. Previously, he worked on various databases at SAP.

Bradley Voytek is an associate professor in the Department of Cognitive Science at UC San Diego and is the inaugural Halıcıoğlu Data Science Institute Fellow. In addition, he’s an Alfred P. Sloan Neuroscience Research Fellow and National Academies Kavli Fellow as well as a founding faculty member of the UC San Diego Data Science program and the Halıcıoğlu Data Science Institute. His research lab studies the computational role that neural oscillations play in coordinating information transfer in the brain. To do this, they combine large-scale data mining and machine learning techniques with hypothesis-driven experimental research. He’s also known for his zombie brain “research” with his friend and fellow neuroscientist Timothy Verstynen, with whom he has published the book Do Zombies Dream of Undead Sheep?

Todd Walter is chief technologist and fellow at Teradata, where he helps business leaders, analysts, and technologists better understand all of the astonishing possibilities of big data and analytics in view of emerging and existing capabilities of information infrastructures. Todd has been with Teradata for more than 30 years. He’s a sought-after speaker and educator on analytics strategy, big data architecture, and exposing the virtually limitless business opportunities that can be realized by architecting with the most advanced analytic intelligence platforms and solutions. Todd holds more than a dozen patents.

Dean Wampler is an expert in streaming data systems, focusing on applications of machine learning and artificial intelligence (ML/AI). He’s head of developer relations at Anyscale, which is developing Ray for distributed Python, primarily for ML/AI. Previously, he was an engineering VP at Lightbend, where he led the development of Lightbend CloudFlow, an integrated system for building and running streaming data applications with Akka Streams, Apache Spark, Apache Flink, and Apache Kafka. Dean is the author of Fast Data Architectures for Streaming Applications, Programming Scala, and Functional Programming for Java Developers, and he’s the coauthor of Programming Hive, all from O’Reilly. He’s a contributor to several open source projects. A frequent conference speaker and tutorial teacher, he’s also the co-organizer of several conferences around the world and several user groups in Chicago. He earned his PhD in physics from the University of Washington.

Jason Wang is a software engineer at Cloudera focusing on the cloud.

Jiao (Jennie) Wang is a software engineer on the big data technology team at Intel, where she works in the area of big data analytics. She’s engaged in developing and optimizing distributed deep learning framework on Apache Spark.

Jiao（Jennie）Wang是英特尔大数据技术团队的软件工程师，主要工作在大数据分析领域。她致力于基于Apache Spark开发和优化分布式深度学习框架。

Luyang Wang is a senior manager on the Burger King guest intelligence team at Restaurant Brands International, where he works on machine learning and big data analytics. He’s engaged in developing distributed machine learning applications and real-time web services for the Burger King brand. Previously, Luyang Wang was at Philips Big Data and AI Lab and Office Depot.

Rachel Warren is a software engineer and data scientist for Salesforce Einstein, where she is working on scaling and productionizing auto ML on Spark. Previously, Rachel was a machine learning engineer for Alpine Data, where she helped build a Spark auto-tuner to automatically configure Spark applications in new environments. A Spark enthusiast, she is the coauthor of High Performance Spark. Rachel is a climber, frisbee player, cyclist, and adventurer. Last year, she and her partner completed a thousand-mile off-road unassisted bicycle tour of Patagonia.

Robin Way is a faculty member for banking at the International Institute of Analytics and the founder and president of management analytics consultancy Corios. Robin has over 25 years of experience in the design, development, execution, and improvement of applied analytics models for clients in the credit, payments, lending, brokerage, insurance, and energy industries. Previously, Robin was a managing analytics consultant in SAS Institute’s Financial Services Business Unit for 12 years and spent another 10+ years in analytic management roles for several client-side and consulting firms. Robin’s professional passion is devoted to democratizing and demystifying the science of applied analytics. His contributions to the field correspondingly emphasize statistical visualization, analytical data preparation, predictive modeling, time series forecasting, mathematical optimization applied to marketing, and risk management strategies. He is author of Skate Where the Puck’s Headed: A Playbook for Scoring Big with Predictive Analytics. Robin holds an undergraduate degree from the University of California at Berkeley; his subsequent graduate-level coursework emphasized the analytical modeling of human and consumer behavior. He lives in Portland, Oregon, with his wife, Melissa, and two sons, Colin and Liam. In his spare time, Robin plays soccer and holds a black belt in taekwondo.

Thomas Weise is a software engineer for the streaming platform at Lyft. He’s also a PMC member for the Apache Apex and Apache Beam projects and has contributed to several more projects within the ASF ecosystem. Thomas is a frequent speaker at international big data conferences and the author of Learning Apache Apex.

Jeffrey Wong is the global chief innovation officer at EY, where he’s challenging everything from the way EY operates internally to how it provides services to its clients. Jeff works across the entire organization to help identify, share, and scale the best ideas and serves the EY Global Innovation team’s remit to research and explore new technologies. He brings deep experience across strategy, investing, and building new ventures globally. Throughout his career, he has built new businesses across various concepts, including local commerce, B2B exchanges, services, mobile, and big data at Boston Consulting Group, JAFCO America Ventures, JP Morgan Partners, and eBay. Jeff sits on the Oxford Foundry Board at Oxford University and the advisory board for AI4All, a nonprofit organization working to increase diversity and inclusion in artificial intelligence. He’s also a member of the World Economic Forum’s Global Future Council on Innovation Ecosystems. Jeff holds an AB in economics, master’s degrees in industrial engineering and engineering management, and an MBA from Stanford University.

Jerry Xu is cofounder and CTO at Datatron Technologies. An innovative software engineer with extensive programming and design experience in storage systems, online services, mobile, distributed systems, virtualization, and OS kernels, Jerry also has a demonstrated ability to direct and motivate a team of software engineers to complete projects meeting specifications and deadlines. Previously, he worked at Zynga, Twitter, Box, and Lyft, where he built the company’s ETA machine learning model. Jerry is the author of open source project LibCrunch. He’s a three-time Microsoft Gold Star Award winner.

Lan is the founding partner of Basis Set Ventures (www.basisset.vc), a ~$140M early stage venture firm focused on the Future of Work through artificial intelligence. Lan built the Corporate Development Strategy team at Dropbox, which was one of the most acquisitive private tech companies during her tenure with 30+ acquisitions. Prior to Dropbox, she worked with McKinsey in New York and Shanghai, advising Fortune 500 companies on issues including big data, AI, and growth strategy. Earlier in her career, Lan was an entrepreneur who built brain training games. She studied human brain functions for her Ph.D. and received her MA in Statistics, both from the University of Michigan.

Boris Yakubchik is a data scientist at Forbes. He creates user-facing products that use machine learning and builds systems from the servers that clean and process data to the frontend that users interact with.

Yuhao Yang is a senior software engineer on the big data team at Intel, where he focuses on deep learning algorithms and applications—particularly distributed deep learning and machine learning solutions for fraud detection, recommendation, speech recognition, and visual perception. He’s also an active contributor to Apache Spark MLlib.

Jeffrey Yau is a distinguished data scientist at WalmartLabs, where he leads data science for the store technology department. Previously, he was the chief data scientist at AllianceBernstein, a global asset-management firm; the vice president and head of data science at Silicon Valley Data Science, where he led a team of PhD data scientists helping companies transform their businesses using advanced data science techniques and emerging technology; the head of risk analytics at Charles Schwab; director of financial risk management consulting at KPMG; assistant director at Moody’s Analytics; and assistant professor of economics at Virginia Tech. Jeffrey’s active in the data science community and often speaks at data science conferences and local events. He has many years of experience in applying a wide range of econometric and machine learning techniques to create analytic solutions for financial institutions, businesses, and policy institutions. Jeffrey holds a PhD and an MA in economics from the University of Pennsylvania and a BS in mathematics and economics from UCLA.

Ting-Fang Yen is the director of research at DataVisor, the leading fraud, crime, and abuse-detection solution using unsupervised machine learning to detect fraudulent and malicious activity such as fake account registrations, fraudulent transactions, spam, account takeovers, and more. She has over 10 years of experience in applying big data analytics and machine learning to tackle problems in cybersecurity. Ting-Fang holds a PhD in electrical and computer engineering from Carnegie Mellon University.

Fang Yu is the cofounder and CTO of DataVisor, where her work focuses on big data for security. Over the past 10 years, Fang has developed algorithms and built systems for identifying various kinds of malicious traffic including worms, spam, bot queries, faked and hijacked account activities, and fraudulent financial transactions. Fang holds a PhD degree from the EECS Department at the University of California, Berkeley.

Ali Zaidi is a PhD student in statistics at UC Berkeley. Previously, he was a data scientist in Microsoft’s AI and Research Group, where he worked to make distributed computing and machine learning in the cloud easier, more efficient, and more enjoyable for data scientists and developers alike. Before that, Ali was a research associate at NERA (National Economic Research Associates), providing statistical expertise on financial risk, securities valuation, and asset pricing. He studied statistics at the University of Toronto and computer science at Stanford University.

Tristan Zajonc is CTO for machine learning at Cloudera. Previously, Tristan led engineering for Cloudera Data Science Workbench and was the cofounder and CEO of enterprise data science platform Sense (acquired by Cloudera in 2016). He has over 15 years’ experience in applied data science, machine learning, and machine learning systems development across academia and industry and holds a PhD from Harvard University.

Salah Zalatimo is the chief digital officer at Forbes, where he leads the product management, design, engineering, audience development and ecommerce groups. He joined the company in 2015 through the acquisition of his startup, Camerama. He has since led a digital transformation, helping generate record traffic and revenues. 

Salah is a leader in the New York tech community, working closely with the NYC Department of Education. He is an active speaker on digital transformation and AI in journalism. He serves on the Media Advisory Board for Quinnipiac University and the board of Haymakers For Hope charity boxing organization.

 Salah holds a BA and MBA from Columbia University. He lives with his wife and two sons in Bed Stuy, Brooklyn.

Jian Zhang is a senior software engineer manager at Intel, where he and his team primarily focus on open source storage development and optimizations on Intel platforms and build reference solutions for customers. He has 10 years of experience doing performance analysis and optimization for open source projects like Xen, KVM, Swift, and Ceph and working with Hadoop distributed file system (HDFS) and benchmarking workloads like SPEC and TPC. Jian holds a master’s degree in computer science and engineering from Shanghai Jiao Tong University.

Yongzheng Zhang is a senior manager of data mining at LinkedIn and an active researcher and practitioner of text mining and machine learning. He’s developed many practical and scalable solutions for utilizing unstructured data for ecommerce and social networking applications, including search, merchandising, social commerce, and customer-service excellence. Yongzheng is a highly regarded expert in text mining and has published and presented many papers in top journals and at conferences. He also organizes tutorials and workshops on sentiment analysis at prestigious conferences. He holds a PhD in computer science from Dalhousie University in Canada.

Yuan Zhou is a senior software development engineer in the Software and Service Group at Intel, where he works on the Open Source Technology Center team primarily focused on big data storage software. He’s been working in databases, virtualization, and cloud computing for most of his 7+ year career at Intel.

Corey Zumar is a software engineer at Databricks, where he’s working on machine learning infrastructure and APIs for model management and production deployment. Corey is also an active contributor to MLflow. He holds a master’s degree in computer science from UC Berkeley. At UC Berkeley’s RISELab, he was one of the lead developers of Clipper, an open source project and research effort focused on high-performance model serving.