Speakers

Safia Abdalla is one of the maintainers of nteract, a desktop-based interactive computing experience. A data scientist and software engineer with an interest in open source software and data science for social good, Safia is the organizer of PyData Chicago. In her free time, she enjoys running, working out, and drinking tea.

Alexandre Archambault is a software and data engineer, and a contributor to or author of various Scala projects, including coursier and shapeless.

Damián Avila is a software development team lead at Anaconda, Inc. A software developer, data scientist, and quantitative analyst from Córdoba, Argentina, his interests include data science, finance, data visualization, and the Jupyter/IPython ecosystem. Damián has made meaningful contributions to several open source projects and is a core developer for popular projects such as Jupyter/IPython, Nikola, and Bokeh. His personal project RISE, a “live” slideshow for the Jupyter Notebook, is quite popular. Damián is a frequent speaker at national and international conferences.

Demba Ba is an assistant professor of electrical engineering and bioengineering at Harvard University, where he directs the CRISP group. He and his group develop mathematical and computational tools to elucidate the role of dynamic networks of neurons in phenomena such as anesthesia, sleep, the learning of fear, and aging and to enable more efficient signal representations that exploit the structure present in natural media such as audio, images, and video. Demba is passionate about teaching, and eagerly incorporates Jupyter notebooks and the Python ecosystem in his courses because of the unique opportunity they provide for interactive, web-based teaching of content that has not traditionally leveraged scientific computing resources. Attempting to bridge the gap that has existed between theory and pen-and-paper courses and application- and coding-focused classes, he spearheaded the development and deployment of the JupyterHub Notebook on Amazon AWS cloud for two classes in Harvard’s School of Engineering and Applied Sciences. In 2016, Demba received a research fellowship in neuroscience from the Alfred P. Sloan Foundation. He holds a BSc in electrical engineering from the University of Maryland, College Park, and both an MSci and a PhD in electrical engineering and computer science with a minor in mathematics from the Massachusetts Institute of Technology.

Gunjan Baid is a student at University of California, Berkeley. She completed her bachelor’s degree in computer science and biochemistry and is now pursuing a master’s degree in computer science with a research focus on computational biology. Gunjan is associated with the undergraduate Data Science education program, where as a student instructor, she worked with Jupyter notebooks in the classroom and now provides technical support for the program’s JupyterHub infrastructure.

Lorena A. Barba is associate professor of mechanical and aerospace engineering at the George Washington University in Washington, DC. In addition to her research in computational science and engineering, she is interested in education technology, social learning, and massively open online courses as well as innovations in STEM education, including flipped classrooms and other forms of blended learning. Lorena is a recipient of the 2016 Leamer-Rosenthal Award for Open Social Sciences and was recognized with an honorable mention at the Open Education Consortium’s 2017 Open Education Awards for Excellence.

James Bednar is a senior solutions architect at Anaconda. Previously, Jim was a lecturer and researcher in computational neuroscience at the University of Edinburgh, Scotland, and a software and hardware engineer at National Instruments. He manages the open source Python projects datashader, HoloViews, GeoViews, ImaGen, and Param. He has published more than 50 papers and books about the visual system, data visualization, and software development. Jim holds a PhD in computer science from the University of Texas as well as degrees in electrical engineering and philosophy.

Daina Bouquin is the head librarian of the Harvard-Smithsonian Center for Astrophysics in Cambridge, MA. Her work aims to lower social and technical barriers that impact the astronomy community’s ability to create and share new knowledge. Her research interests focus primarily on how libraries can support open science, research software preservation, emerging computational methods, and the history of science. Daina is currently working toward an MS in data analytics at CUNY’s School of Professional Studies.

Maarten Breddels is a astronomer, freelance developer, consultant, and data scientist working working mostly with Python, C++, and JavaScript in the Jupyter ecosystem. His expertise ranges from fast numerical computation and API design to 3D visualization. He holds a bachelor’s degree in ICT and both a master’s degree and PhD in astronomy.

Matt Burton is a visiting assistant professor at the School of Computing and Information at the University of Pittsburgh. His research interests include infrastructure studies, data science, and scholarly communication. Matt holds a PhD in information from the University of Michigan. His dissertation, Blogs as Infrastructure for Scholarly Communication, explored digital humanities blogging and the sociotechnical dynamics of web-centric publishing.

Natalino Busa is the chief data architect at DBS, where he leads the definition, design, and implementation of big, fast data solutions for data-driven applications, such as predictive analytics, personalized marketing, and security event monitoring. Natalino is an all-around technology manager, product developer, and innovator with a 15+-year track record in research, development, and management of distributed architectures and scalable services and applications. Previously, he was the head of data science at Teradata, an enterprise data architect at ING, and a senior researcher at Philips Research Laboratories on the topics of system-on-a-chip architectures, distributed computing, and parallelizing compilers.

Matthias Bussonnier is postdoc at UC Berkeley BIDS and a core developer of the Jupyter and IPython project, where he is working in close collaboration with Google to bring real-time collaboration to the Jupyter environment.

Charlotte Cabasse-Mazel is an ethnographer at the Berkeley Institute for Data Science at UC Berkeley. She is interested in the ways in which practices and methodologies of data science transform production of knowledge and interdisciplinary collaboration, as well as scientific personae and trajectories within the academic institution. Charlotte holds a PhD in geography and science and technologies studies from the University of Paris-Est, where she studied at the Laboratoire Techniques, Territoires et Sociétés (LATTS), at Ecole Nationale des Ponts et Chaussées.

Brett Cannon is a Python core developer working on Python on the Azure Data Science Tools team at Microsoft.

Shane Canon is a project engineer in the Data and Analytics Services group at NERSC in the Lawrence Berkeley National Laboratory, where he focuses on enabling data-intensive applications on HPC platforms and engaging with bioinformatics applications. Shane has held a number of positions at NERSC, including leading the Technology Integration group, where he focused on the Magellan Project and other areas of strategic focus, leading the Data Systems group, and serving as a system administrator for the PDSF cluster, where he gained experience in cluster administration, batch systems, parallel filesystems, and the Linux kernel. He was also a group leader at Oak Ridge National Laboratory, where he architected the 10 petabyte Spider filesystem. Shane is involved in a number of projects outside of NERSC, including serving as the production lead on the KBase project, which is developing a platform to enable predictive biology. Shane holds a PhD in physics from Duke University and a BS in physics from Auburn University.

Prithwish Chakraborty is a data scientist on the IBM Watson for Real World Evidence team at IBM Watson Health. His work focuses on applications of data science towards patient health characterization and risk modeling. Broadly, his research interests are temporal data mining, machine learning, and image recognition. His work has been published in key data science venues, including KDD, SDM, and AAAI, and he presented a tutorial on public health forecasting in AAAI 2016 and gave an invited talk at BCDE 2014. Prithwish holds a patent with HP labs on forecasting solar photovoltaic output. He holds a PhD in computer science from Virginia Tech, where his research, under the guidance of Naren Ramakrishnan, focused on the applications of data science to public health forecasting.

Born and raised in Taiwan, Hope Chen is a PhD candidate in astronomy and astrophysics at Harvard University. Since 2011, Hope has been a member of the Star Formation research group led by Alyssa A. Goodman of Harvard and has embarked on several research projects aimed at decoding the mysteries of structural formation in nearby cradles of stars, such as the Gould Belt molecular clouds. Hope is interested in making astronomy seamless and accessible and has been an ardent user of the Jupyter Notebook. Hope holds a degree from National Tsing Hua University with the highest distinction, the Dr. Mei Yi-Chih Prize.

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.

Shreyas Cholia leads the Usable Software Systems group at Lawrence Berkeley National Laboratory (LBNL), which focuses on making scientific computing more transparent and usable. He is particularly interested in how web APIs and tools can facilitate this. Shreyas also leads the science gateway, web, and grid efforts at the National Energy Research Scientific Computing Center (NERSC) at LBNL. His current work includes a project that enables Jupyter to interact with supercomputing resources, and NEWT, a REST API for high-performance computing. He holds a degree from Rice University, where he studied computer science and cognitive sciences.

Danielle Chou is a solutions engineer at Zymergen, where she works on custom software tools for scientists. Previously, she worked on failure detection software for an ingestible sensor company and studied bioengineering at UC Berkeley and UCSF.

Pramit Choudhary is a Lead data scientist/ML scientist at h2o.ai, where he focuses on optimizing and applying classical machine learning and Bayesian design strategy to solve large scale real-world problems.
Currently, he is leading initiatives on figuring out better ways to generate a predictive model’s learned decision policies as meaningful insights(Supervised/Unsupervised problems)

Rowan Cockett is the founder and CTO of 3point Science (acquired by Aranz Geo in 2016), a company building web-based visualization software for the geoscience industry, including Steno3D. Rowan is also a graduate student at the University of British Columbia, where he is researching a numerical framework aimed at increasing quantitative communication in the geosciences developed through his studies on numerical geophysics, subsurface flow, and structural geology. Rowan is interested in the intersection of education, industry, and academia and seeing what happens when you make powerful scientific modeling, visualization, and communication tools accessible through the web. Much of his research is accessible through an open source software initiative for geophysical simulations and parameter estimation (SimPEG) and an open website for geoscience modeling (Visible Geology).

Chris Colbert is a software architect for Project Jupyter.

Sylvain Corlay is the founder of QuantStack and a quant researcher specializing in stochastic analysis and optimal control. Previously, Sylvain was a quant researcher at Bloomberg LP and an adjunct faculty member at Columbia University and NYU. As an open source developer, Sylvain mostly contributes to Project Jupyter in the area of interactive widgets and lower-level components such as traitlets. He is also a member of the steering committee of the project. Sylvain is also a contributor to a number of other open source projects for scientific computing and data visualization, such as bqplot, pythreejs, and ipyleaflet, and coauthored the xtensor C++ tensor algebra library. He holds a PhD in applied mathematics from University Paris VI.

John DeBlase is lead developer for the CUNY Building Performance Lab, where he helps develop Python-based statistical modeling applications for city-wide energy management research. A developer, data scientist, and musician from Queens, NY, John’s personal research revolves around the development musical intelligence systems using natural language processing techniques with a focus on real-time human-computer interaction. John is interested in developing applications for data scientists that emphasize interactive data visualization, leveraging the best tools currently available in both Python and Node.js.

Christine Doig is a senior product manager and data scientist at Anaconda Powered by Continuum Analytics. Christine has 8+ years of experience in analytics, operations research, and machine learning in a variety of industries, including energy, manufacturing, and banking. An open source advocate, she has spoken at PyData, EuroPython, SciPy, PyCon, OSCON, and many other open source conferences. Christine holds an MS in industrial engineering from the Polytechnic University of Catalonia in Barcelona.

Nadia Eghbal works on community programs at GitHub, where she is building sustainability initiatives. Nadia explores how we can better support open source infrastructure, highlighting current gaps in funding and knowledge. She recently published Roads and Bridges: The Unseen Labor Behind Our Digital Infrastructure with support from the Ford Foundation. Nadia is based in San Francisco.

Lori Eich is a senior product manager at Civis Analytics, where she works with engineers to build the Civis Data Science Platform. Lori’s background is in software engineering, derivatives trading, environmental consulting, and competitive fringe sports. She holds an SM and SB in Earth, atmospheric, and planetary sciences from the Massachusetts Institute of Technology.

Faisal Farooq is the principal scientist in the Watson Health group of IBM Watson, where he works on next-generation healthcare software to improve patient care. Faisal is an expert in applying machine learning in the healthcare domain. Previously, he was a senior key expert (distinguished scientist) at Siemens Healthcare, where he successfully delivered the most widely adopted data science product in US healthcare. Faisal has published a number of papers in multiple journals and at conferences in the areas of machine learning, handwriting, biometrics, and text analysis. He holds a PhD in computer science and engineering from the University at Buffalo, where he worked as a graduate research assistant in Center of Excellence for Document Analysis and Recognition (CEDAR) and the Center for Unified Biometrics and Sensors (CUBS). He also completed multiple research internships at the IBM T.J. Watson Research Center.

Felipe Ferreira is a big data engineer at Globo.com, where he focuses on big data platform analytics using Hadoop and associated ecosystem tools. Felipe is an analytical, performance-focused engineer with over 12 years of experience in enterprise systems development and architectural design using JEE technology combined with the ability to drive user-centric solutions, define strategy, and lead data management.

Jeremy Freeman is manager of computational biology at the Chan Zuckerberg Initiative, where he is helping develop efforts to support and accelerate basic research with tools for analysis, visualization, and collaborative sharing of data and knowledge. Previously, he ran a neuroscience research lab for several years. A scientist at the intersection of biology and technology, Jeremy wants to understand how biological systems work and use that understanding to benefit both human health and the design of intelligent systems. He is passionate about open source and open science and bringing scientists and engineers together across a range of fields.

Tim Gasper is Director of Product at data.world, the cloud data catalog company and largest open data community in the world. With over a decade of experience in product management, Tim has spent his entire career helping companies gain value from their data. He previously ran data product management for Janrain (now Akamai Identity Cloud), led product and marketing for Bitfusion, an artificial intelligence (AI) software company, led product for Rackspace’s Hadoop and NoSQL as a Service, and managed global offerings for CSC (now known as DXC) Big Data & Analytics business unit. Prior to that he was VP of Product at Infochimps, an enterprise big data cloud services company, acquired by CSC in 2013. Tim is a Case Western Reserve University alumnus, and writes and speaks on entrepreneurship, big data, data governance, and AI.

Laurent Gautier is a scientific research lead at Verily Life Sciences (fka Google Life Sciences). Laurent’s work focuses on data science, visualization, machine learning, data mining, and prototyping software to understand molecular, cellular, and clinical data. He is the author of popular open source tools in bioinformatics and statistical programming for applications in healthcare, life sciences, and beyond and has contributed to or led a number of open source projects, including Bioconductor, affy, and rpy2.

R. Stuart Geiger is an ethnographer and postdoctoral scholar at the Berkeley Institute for Data Science at UC Berkeley, where he studies the infrastructures and institutions that support the production of knowledge. He uses ethnographic, historical, qualitative, and quantitative methods in his research, which is grounded in the fields of computer-supported cooperative work, science and technology studies, and communication and new media studies. He holds a PhD from the UC Berkeley School of Information, where his research focused on the governance and operation of Wikipedia and scientific research networks. He has also studied newcomer socialization, moderation and quality control, specialization and professionalization, cooperation and conflict, the roles of support staff and technicians, and diversity and inclusion.

Brian Granger is an associate professor of physics and data science at Cal Poly State University in San Luis Obispo. Brian is a leader of the IPython project, cofounder of Project Jupyter, and an active contributor to a number of other open source projects focused on data science in Python. Recently, he cocreated the Altair package for statistical visualization in Python. He is an advisory board member of NumFOCUS and a faculty fellow of the Cal Poly Center for Innovation and Entrepreneurship.

Matt Greenwood is the chief innovation officer at Two Sigma Investments, where he has led company-wide efforts across both engineering and modeling teams. Matt oversees development of BeakerX, which extends the Jupyter Notebook to support to six languages, additional widgets, and one-click publication. Matt is also a board member and Venture Partner at Two Sigma Ventures and works closely with portfolio companies in both board membership and advisory capacities. Matt began his career at Bell Labs and later moved to IBM Research, where he was responsible for early efforts in tablet computing and distributed computing. Matt was also lead developer and manager at Entrisphere, where he helped create a product providing access equipment for broadband service providers. Matt holds a PhD in mathematics from Columbia University, where he taught for many years, as well as a BA and MA in math from Oxford University and an MA in theoretical physics from the Weizmann Institute of Science in Israel.

Jason Grout is a Jupyter developer at Bloomberg, working primarily on JupyterLab and the interactive widget system. Previously, Jason was an assistant professor of mathematics at Drake University in Des Moines, Iowa. Jason co-organizes the PyDataNYC Meetup. He has also been a major contributor to the open source Sage mathematical software system for many years. He holds a PhD in mathematics from Brigham Young University.

Mark Hahnel is the founder of figshare, an open data tool that allows researchers to publish all of their data in a citable, searchable, and sharable manner. Mark is passionate about open science and the potential it has to revolutionize the research community. He’s fresh out of academia, having just completed his PhD in stem cell biology at Imperial College London. Mark also studied genetics in Newcastle and Leeds.

Jess Hamrick is a PhD candidate at UC Berkeley. Her research studies how people use imagination to solve problems and reason about the world and how to apply those ideas to machine learning and artificial intelligence. Jess is a member of the Jupyter Steering Council and is the lead maintainer of nbgrader, an open source tool for creating and grading assignments in the Jupyter Notebook. She holds a BS and an MEng in computer science from MIT.

Lindsey Heagy is a PhD candidate at the University of British Columbia studying numerical geophysics. Her work focuses on using electromagnetic geophysics for monitoring subsurface injections, including carbon capture and storage and hydraulic fracturing. She a project lead on GeoSci.xyz, an effort to build collaborative, interactive, web-based textbooks in the geosciences, and a core contributor to SimPEG, an open source framework for geophysical simulation and inversions.

Paul Ivanov is a member of the Jupyter Steering Council and a senior software engineer at Bloomberg LP working on IPython- and Jupyter-related open source projects. Previously, Paul worked on backend and data engineering at Disqus; was a code monkey at the Brain Imaging Center at UC Berkeley, where he worked on IPython and taught at UC Berkeley’s Python bootcamps; worked in Bruno Olshausen’s lab at the Redwood Center for Theoretical Neuroscience; and was a PhD candidate in the Vision Science program at UC Berkeley. He holds a degree in computer science from UC Davis.

Kari Jordan is the deputy director of assessment for Data Carpentry and an advocate for improving diversity in data science. Previously, Kari was a postdoctoral fellow at Embry-Riddle Aeronautical University, where her research focus was evidenced-based instructional practices among STEM faculty. Kari served on the board of directors for the National Society of Black Engineers (NSBE) for three years. A product of the Detroit Public School system, Kari holds a BS and an MS in mechanical engineering from Michigan Technological University and a PhD in engineering education from the Ohio State University. During her education, she interned with Marathon Petroleum Company, SC Johnson, Ford Motor Company, and Educational Testing Services. As a graduate student, she received fellowships from the National Society of Black Engineers (NSBE), King-Chavez-Parks Initiative, and the National GEM Consortium.

Wendy Kan is a data scientist at Kaggle, the largest global data science community, where she works with companies and organizations to transform their data into machine learning competitions. Previously, Wendy was a software engineer and researcher. She holds BS and MS degrees in electrical engineering and a PhD in biomedical engineering.

Kyle Kelley is a senior software engineer at Netflix, a maintainer on nteract.io, and a core developer of the IPython/Jupyter project. He wants to help build great environments for collaborative analysis, development, and production workloads for everyone, from small teams to massive scale.

Chris Kotfila is an R&D engineer at Kitware. Chris’s research interests are in natural language processing, machine learning, knowledge organization and geographic information science. He holds dual degrees in computer science and philosophy from Rensselaer Polytechnic Institute and a master’s degree in library science, where he focused on issues of open access, scholarly communication and reproducible research. During his time at RPI, he worked regularly as a research programmer in the area of computational cognitive engineering. Chris also served overseas with the US Peace Corps. He is an avid open source enthusiast and a hopeless Emacs user.

Aaron Kramer is a data scientist and engineer at DataScience.com, where he builds powerful language and engagement models using natural language processing, deep learning, Bayesian inference, and machine learning.

Michael Lanzetta is a principal SDE at Microsoft. In his more than 20-year career in the software industry, he’s worked in domains as varied as circuit design and drug discovery and in languages from JavaScript to F#, but his primary focus has always been scaled-out server-side work. Michael has a background in demand forecasting from Manugistics and Amazon and machine learning from Bing; he has spent the last few years building intelligent services on Azure using everything from Spark to TensorFlow and CNTK.

Ryan Lovett manages research and instructional computing for the Department of Statistics at UC Berkeley and is a member of the Data Science Education Program’s infrastructure team. He is most often a sysadmin, though he also enjoys programming and consulting with faculty and students.

Yoshi Nobu Masatani is a project researcher at the National Institute of Informatics, an inter-university research institute for information and systems, where he is responsible for the design and operation of the academic cloud within NII. These years his team utilizes Jupyter for DevOps on NII’s cloud as Literate Computing practices. He has a broad range of experience with OSS-based infrastructure deployments and operations with high-availability systems and big data clusters. Previously, Nobu was a senior specialist and manager of OSS professional services within a large IT company.

Johan Mabille is a scientific software developer at QuantStack, where he specializes in high-performance computing in C++. Previously, Johan was a quant developer at HSBC. An open source developer, Johan is the coauthor of xtensor and xeus and the main author of xsimd. He holds a master’s degree in computer science from Centrale-Supelec.

Ali Marami has PhD in Finance from University of Neuchâtel in Switzerland and BS in Electrical engineering. He has extensive experience in financial and quantitative modeling and model risk management in several US banks. He is the Chief Data Scientist and of the founders of R-Brain which is a platform for developing, sharing and promoting models and applications in Data Science.

Wes McKinney is a software architect at Two Sigma Investments. He is the creator of Python’s pandas library and a PMC member for Apache Arrow and Apache Parquet. He wrote the book Python for Data Analysis. Previously, Wes worked for Cloudera and was the founder and CEO of DataPad.

Romain Menegaux is a researcher on the Quantitative Financial Research team at Bloomberg LP, where he develops derivatives pricing models and applies machine learning to a variety of financial problems. Romain is one of the main developers of bqplot and an occasional contributor to ipywidgets.

William Merchan is the chief strategy officer at DataScience.com, where he leads business and corporate development, partner initiatives, and strategy. Previously, he served as senior vice president of strategic alliances and general manager of dynamic pricing at MarketShare, where he oversaw global business development and partner relationships and successfully led the company to a $450 million acquisition by Neustar.

Daniel Mietchen is a biophysicist interested in integrating research workflows with the World Wide Web, particularly through open licensing, open standards, public version histories, and forkability. With research activities spanning from the subcellular to the organismic level, from fossils to developing embryos and from insect larvae to elephants, he has experienced multiple shades of the research cycle and a variety of approaches to collaboration and sharing in research contexts. He has also been contributing to Wikipedia and its sister projects for more than a decade and is actively engaged in increasing the interactions between the Wikimedia and research communities.

Christian Moscardi is director of technology for the Data Incubator. Previously, Christian developed a CMS for food blogs, worked for Google, and researched and taught at Columbia. He organizes with BetaNYC, New York’s civic tech organization, and contributes to various civic data projects. His extracurricular activities include cooking, playing the piano, and exploring New York.

Andreas Müller is a lecturer at the Data Science Institute at Columbia University and author of Introduction to Machine Learning with Python (O’Reilly), which describes a practical approach to machine learning with Python and scikit-learn. His mission is to create open tools to lower the barrier of entry for machine learning applications, promote reproducible science, and democratize the access to high-quality machine learning algorithms. Andreas is one of the core developers of the scikit-learn machine learning library and has been comaintaining it for several years. He is also a Software Carpentry instructor. Previously, he worked at the NYU Center for Data Science on open source and open science and as a machine learning scientist at Amazon.

Diogo Munaro Vieira is a big data engineer at Globo.com. He is experienced in web development, P2P networking, collaborative systems, recommendation systems, open source software, and business intelligence. Diogo holds a bachelor’s degree in biological science and bioinformatics and a master’s degree in artificial intelligence from Universidade Federal do Rio de Janeiro.

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.

Andrew Odewahn is the CTO of O’Reilly Media, where he helps define and create the new products, services, and business models that will help O’Reilly continue to make the transition to an increasingly digital future. The author of two books on database development, he has experience as a software developer and consultant in a number of industries, including manufacturing, pharmaceuticals, and publishing. Andrew holds an MBA from New York University and a degree in computer science from the University of Alabama. He’s also thru-hiked the Appalachian Trail from Georgia to Maine.

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.

Yuvi Panda is infrastructure lead for the Data Science Education Program at UC Berkeley, where he works on scaling JupyterHub for use by thousands of students. A programmer and DevOps engineer, he wants to make it easy for people who don’t traditionally consider themselves programmers to do things with code and builds tools (Quarry, PAWS, etc.) to sidestep the list of historical accidents that constitute the “command-line tax” that people have to pay before doing productive things with computing. He’s a core member of the JupyterHub team and works on mybinder.org as well. Yuvi is also a Wikimedian, since you can check out of Wikimedia, but you can never leave.

Hilary Parker is a data scientist at Stitch Fix and cofounder of the Not So Standard Deviations podcast. Hilary focuses on R, experimentation, and rigorous analysis development methods such as reproducibility. Previously, she was a senior data analyst at Etsy. Hilary holds a PhD in biostatistics from the Johns Hopkins Bloomberg School of Public Health. Hilary can be found on Twitter at @hspter.

Fernando Pérez is a staff scientist at Lawrence Berkeley National Laboratory and a founding investigator of the Berkeley Institute for Data Science at UC Berkeley, created in 2013. His research focuses on creating tools for modern computational research and data science across domain disciplines, with an emphasis on high-level languages, interactive and literate computing, and reproducible research. He created IPython while a graduate student in 2001 and continues to lead its evolution into Project Jupyter, now as a collaborative effort with a talented team that does all the hard work. Fernando regularly lectures about scientific computing and data science and is a member of the Python Software Foundation, a founding member of NumFOCUS, and a National Academy of Science Kavli Frontiers of Science Fellow. He is also the recipient of the 2012 Award for the Advancement of Free Software from the Free Software Foundation. Fernando holds a PhD in particle physics from the University of Colorado at Boulder, which he followed with postdoctoral research in applied mathematics and developing numerical algorithms.

Fabio Pliger is the technical lead for Anaconda Fusion and a Bokeh core developer at Anaconda Powered by Continuum Analytics, where he also worked on the XDATA DARPA and on customer projects. Fabio has 14+ years of experience in Python applied to both highly regulated enterprise and open source. He has been an open source and Python advocate for many years and has spoken at many tech conferences around the world. He is a former chairman of the EuroPython Society, cochair of the EuroPython Conference and PyCon Italy, and cofounder of the Python Italia Association. Fabio holds an bachelor’s degree in computer science from the University of Verona, Italy.

Cheryl Quah is a senior software engineer at Bloomberg LP, where she develops applications to improve financial professionals’ research and investment workflows.

Min Ragan-Kelley is a postdoctoral fellow at Simula Research Lab in Oslo, Norway, where he focuses on developing JupyterHub, Binder, and related technologies and supporting deployments of Jupyter in science and education around the world. Min has been contributing to IPython and Jupyter since 2006 (full-time since 2013).

Subbu Rama is cofounder and CEO at Bitfusion, a company providing tools to make deep learning and AI application development and infrastructure management faster and easier. Previously, Subbu held various roles at Intel, leading engineering efforts spanning design, automation, validation, and postsilicon. He worked on Intel’s first integrated-graphics CPU, Intel’s first low-power CPU, Atom, and its SOC, high-performance microservers (Intel’s first initiative on microservers using low-power mobile phone processors), and Xeon servers. Subbu also led Dell Innovation Labs, driving innovation and skunk works, later overseeing numerous new strategic technology initiatives at the intersection of software and the cloud. There he built an engineering team from the ground up and launched Dell’s first cloud infrastructure marketplace.

Bernie Randles is a graduate student in the Information Studies program at UCLA. Her work is centered around knowledge creation in astronomy, specifically examining astronomers’ data and software pipeline practices. She also researches the use of open source software in scientific research organizations, primarily in data-rich and computationally intensive fields. Previously, Bernie worked in IT (wearing many hats, some red) at several colleges and universities. She holds degrees in math, computer science, and fine arts.

Megan Risdal is a marketing manager at Kaggle. She holds master’s degrees in linguistics from the University of California, Los Angeles, and North Carolina State University. Her curiosities lie at the intersection of data, science, language, and learning.

Mac Rogers is a research engineer at Domino Data Lab, where he helps teams at enterprise companies, nonprofits, and universities accelerate research and integrate predictive models into their business using Domino’s data science platform. Previously, Mac was an investment engineer focusing on equity research systemization at systematic investment management firm Bridgewater Associates.

Ian Rose is as postdoctoral fellow at the Berkeley Institute for Data Science, where he works on the Jupyter Project. He holds a PhD in geology from UC Berkeley, where his research focused on the physics of the deep Earth.

Philipp Rudiger is a software developer at Anaconda, where he develops open source and client-specific software solutions for data management, visualization, and analysis. Philipp holds a PhD in computational modeling of the visual system.

Patty Ryan leads prototyping engagements with partners, both large and small, on the Technology Evangelism and Development team at Microsoft. She specializes in designing and operationalizing predictive models that inform strategies, focus customer outreach, and increase engagement. Previously, Patty led telemetry, analytics, UX, and support in Dynamics, Azure Identity, and O365, driving innovation in customer-facing self-service and distributed analytics.

Zach Sailer is graduate student at the Harms Lab at the University of Oregon, where he studies the mechanisms that shape protein evolution from a biophysical perspective. Previously, he was a core developer for the IPython/Jupyter team at Cal Poly San Luis Obispo. Zach has created and contributed to various scientific open source projects and is also a strong advocate for open science, working hard to promote and practice open science in all aspects of his research.

Scott Sanderson is a senior software engineer at Quantopian, where he is responsible for the design and implementation of Quantopian’s backtesting and research APIs. Within the Jupyter ecosystem, most of Scott’s work focuses on enhancing the extensibility of the Jupyter Notebook for use in large deployments.

Kaz Sato is a staff developer advocate on the cloud platform team at Google, where he leads the developer advocacy team for machine learning and data analytics products such as TensorFlow, the Vision API, and BigQuery. Kaz has been leading and supporting developer communities for Google Cloud for over seven years. He’s a frequent speaker at conferences, including Google I/O 2016, Hadoop Summit 2016 San Jose, Strata + Hadoop World 2016, and Google Next 2015 NYC and Tel Aviv, and he has hosted FPGA meetups since 2013.

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.

Skipper Seabold is Director of Data Science at Civis Analytics, a data science software and services company. He leads product-facing data science research and development, directing a large and diverse team of data scientists in building core exploratory and modeling software for the Civis Data Science Platform. Prior to Civis, Skipper worked at DataPad (acquired by Cloudera). He’s an economist by training and has a decade of experience working in the Python data community. He started and led the statsmodels Python project, was formerly on the core pandas team, and has contributed to many packages in the Python data stack. He holds strong opinions about writing and barbecue.

Leah Silen has been the executive director of NumFocus from its beginning and worked with the founding board members to write the application for NumFocus’s nonprofit status. Previously, Leah was a public relations and program director in the nonprofit sector, where she focused on community relations and fundraising. Leah has volunteered and sat on several boards of nonprofit organizations.

Steven Silvester is a software engineer at Anaconda Powered by Continuum Analytics, where he works on Project Jupyter and JupyterLab, a next-generation user interface for the Jupyter Notebook. He has also written kernels for Octave, MATLAB, and Scilab. Previously, Steven served 10 years in the US Air Force.

Raj Singh is a developer advocate for IBM Cloud Data Services. Raj pioneered web mapping as a service in the late 1990s with his startup Syncline. Previously, Raj worked on geospatial data interoperability challenges for the Open Geospatial Consortium, an international standards body. He’s a frequent speaker on interoperability and geolocation services and contributed to Mapping Hacks. He holds a PhD from MIT, where his research explored the potential of web services to power urban information systems.

Lee Stott is CTO of academic engagements at Microsoft, where he engages academic institutions across the UK in the ongoing development of the Microsoft platform. Lee has held a number of roles at Microsoft, including academic and technical evangelist. Previously, Lee was the head of information systems at the University of Manchester, where he led service and delivery teams across both academic and commercial markets. Lee holds a PGCE in higher education management from the University of Southampton and an MSc in information technology from the University of Liverpool.

Srinivas Sunkara is a quant on the Quantitative Financial Research team at Bloomberg LP, where he works on developing financial models that apply machine learning techniques to various problems in finance. Srinivas is one of the main developers of bqplot, a Jupyter Notebook–based interactive plotting library, and contributes to other open source projects, including ipywidgets and traitlets.

Vinitra Swamy graduated two years early with a bachelor’s degree in computer science from the University of California, Berkeley, and is now working toward a master’s degree in computer science. Her research interests include data science, cloud computing environments, and natural language processing. Vinitra is head student instructor for Berkeley’s new Foundations of Data Science course, helping shape curriculum and educating thousands of students from diverse backgrounds. Her efforts in data science education were recently recognized with a Berkeley EECS award of excellence in teaching and leadership. Vinitra also leads a Jupyter development student research team within the Data Science Education program and assists with the technical deployment and use of JupyterHub infrastructure campus-wide.

Thorin Tabor is a software engineer at UCSD and a contributing scientist at the Broad Institute. He is the lead developer of the GenePattern Notebook and an open source developer on the integration of bioinformatic tools with Jupyter.

David Taieb is the STSM for the Cloud Data Services Developer Advocacy team at IBM, where he leads a team of avid technologists with the mission of educating developers on the art of possible with cloud technologies. He’s passionate about building open source tools, such as the PixieDust Python library for the Jupyter Notebook and Apache Spark, that help improve developer’s productivity and overall experience. Previously, David was the lead architect for the Watson Core UI and Tooling team based in Littleton, Massachusetts, where he led the design and development of a Unified Tooling Platform to support all the Watson Tools, including accuracy analysis, test experiments, corpus ingestion, and training data generation. Before that, he was the lead architect for the Domino Server OSGi team responsible for integrating the eXpeditor J2EE Web Container in Domino and building first-class APIs for the developer community. David started with IBM in 1996, working on various globalization technologies and products including Domino Global Workbench and a multilingual content management system for the Websphere Application Server. David enjoys sharing his experience by speaking at conferences and meeting as many people as possible. You’ll find him at various events like the Strata Data Conference, Velocity, and IBM Interconnect.

Andy Terrel is president of NumFOCUS. He is also the chief data scientist of REX Real Estate, where he brings his experience building smart, scalable data systems to the real estate industry. A data architect, computational scientist, and technical leader, Andy is a passionate advocate for open source scientific codes and has been involved in the wider scientific Python community since 2006, contributing to numerous projects in the scientific stack.

Andrew Therriault is the chief data officer for the City of Boston, where he leads Boston’s Analytics team, a nationally recognized leader in using data science to improve city operations and make progress in critical areas such as public safety, education, transportation, and health. Previously, Andrew was director of data science for the Democratic National Committee and served as editor of Data and Democracy: How Political Data Science Is Shaping the 2016 Elections from O’Reilly. He holds a PhD in political science from NYU and completed a postdoctoral research fellowship at Vanderbilt.

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×.

Rollin Thomas is a big data architect in the Data and Analytics Services group at Lawrence Berkeley National Laboratory. Previously, he was a staff scientist in the Computational Research division. Rollin has worked on numerical simulations of supernova atmospheres, observation and analysis of supernova spectroscopy data, and data management for supernova cosmology experiments. He has served as a member of the Nearby Supernova Factory, is a builder on the Dark Energy Survey, and is a full member of the Large Synoptic Survey Telescope Dark Energy Science Collaboration. Rollin holds a BS in physics from Purdue University and a PhD in astrophysics from the University of Oklahoma.

Marius Tulbure is a developer and JavaScript enthusiast at figshare, always looking to evolve and improve his code and skills. If asked, he’ll list his hobbies as “everything,” but for the sake of brevity, they include binge-watching TV series and movies, playing his electric guitar, and trying to solve all sorts of hacking puzzles.

Peter Wang is the cofounder and CTO of Anaconda, where he leads the product engineering team for the Anaconda platform and open source projects including Bokeh and Blaze. Peter’s been developing commercial scientific computing and visualization software for over 15 years and has software design and development experience across a broad variety of areas, including 3-D graphics, geophysics, financial risk modeling, large data simulation and visualization, and medical imaging. As a creator of the PyData conference, he also devotes time and energy to growing the Python data community by advocating, teaching, and speaking about Python at conferences worldwide. Peter holds a BA in physics from Cornell University.

Christopher Wilcox is a software engineer at Microsoft, where he works on a range of products including Azure Notebooks, Python Tools for Visual Studio, and the Azure SDK for Python. Chris has more than five years’ experience building developer tooling and, more recently, scalable web services. In his spare time, he races motorcycles, hikes, and explores the Seattle brewing scene.

Karlijn Willems is a journalist at DataCamp, where she focuses on data science and data science education. Previously, she worked as a junior big data developer with Hadoop, Spark, and Scala. Karlijn holds a degree in literature and linguistics (English and Spanish) and information management from KU Leuven.

Carol Willing is a research software engineer at Cal Poly San Luis Obispo working full-time on Project Jupyter, a Python Software Foundation fellow and former director, a Jupyter Steering Council member, a geek in residence at FabLab San Diego, where she teaches wearable electronics and software development, and an independent developer of open hardware and software. She co-organizes PyLadies San Diego and San Diego Python, contributes to open source community projects, including OpenHatch, CPython, Jupyter, and AnitaB.org’s open source projects, and is an active member of the MIT Enterprise Forum in San Diego. She enjoys sharing her passion for electronics, software, problem solving, and the arts. Previously, Carol worked in software engineering management, product and project management, sales, and the nonprofit sector. She holds an MS in management with an emphasis on applied economics and high-tech marketing from MIT and a BSE in electrical engineering from Duke University.