Brought to you by NumFOCUS Foundation and O’Reilly Media Inc.
The official Jupyter Conference
August 22-23, 2017: Training
August 23-25, 2017: Tutorials & Conference
New York, NY

About JupyterCon

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Experience JupyterCon | Who Should Attend | Why Attend | Kudos | Program Chairs & Program Committee | Advisory Committee

JupyterCon will bring together data scientists, business analysts, researchers, educators, developers, and core Project contributors and tool creators in NYC for in-depth training, insightful keynotes, networking events, and practical talks exploring the Project Jupyter platform. JupyterCon focuses on real-world practices and how to successfully implement interactive computation in your workflow and projects. In just four days you’ll discover the best practices for collaborative and reproducible data science; new use cases, and the expertise you need to transform your workflow with Jupyter Notebooks.

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Experience JupyterCon

JupyterCon will educate and motivate by offering:

  • Sessions that apply to the full range of Jupyter's languages and platforms
  • Practical tutorials that go deep into technical skills, new features and applications, and best practices
  • Visionary keynote presentations
  • Immersive, hands-on training courses
  • Unparalleled access to core Project contributors and tool creators
  • A Sponsor Pavilion packed with related projects and products
  • A vibrant "hallway track" where hundreds of programmers, data scientists, analysts, researchers, vendors, and users of all levels discuss important issues
  • Fun evening events and plenty of informal networking
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Who Should Attend

JupyterCon is for anyone who wants to better use Jupyter's tools, including:

  • Developers and programmers
  • Data scientists
  • Business analysts
  • Researchers
  • Educators
  • Users across all disciplines: Science, Engineering, the Arts, Digital Humanities, Digital Studies, Journalism, Library Science, and more
  • System admins
  • Hackers and geeks
  • Enterprise developers and managers
  • Community leaders and managers
  • Companies building products and services for the open source ecosystem

Project Jupyter and O'Reilly Media are committed to promoting diversity and to creating a safe and productive environment for everyone at JupyterCon, and at all of our events. Read the JupyterCon code of conduct.

Why Attend?

In four information-packed days JupyterCon gives you the tools you need to make more effective use of the rich Jupyter ecosystem:

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  • Discover the advantages of using powerful, interactive tools and systems in all your projects that involve computation and data
  • Learn how to develop custom tools that extend the Jupyter platform with new functionality that fits your specific needs (and discover great extensions created by others)
  • See how others make their computational work more robust and reproducible
  • Survey the landscape of educational materials available using Jupyter
  • Learn about how to best deploy the Jupyter platform across your organization in an optimal way, from a small research or educational group to a large environment with customized authentication, cloud resources, and more
  • Find out how to migrate from expensive commercial installations to a more efficient, cost-effective, open source solution
  • Hear about the new directions of the Project and help shape its evolution with your own insights, use cases, and ideas.
  • Receive hype-free guidance to help identify when Jupyter can be a good fit (or not!) for your organization and needs

What people are saying about JupyterCon

JupyterCon was absolutely the best tech conference I've ever been to. There was a perfect mixture of networking, technical talks, and insight. I will 100% be attending next year! ”
—Tim Dobbins, The General Auto Insurance
JupyterCon was the most interesting conference I've been to. Very much focused on analysis development.”
—Hilary Parker
JupyterCon 2017 has been the best conference I have attended in the last decade. I really enjoyed the experience. Looking forward to attend JupyterCon 2018.”
—Kevin Miller (PhD), The University of the West Indies, Mona, Kingston, Jamaica
JupyterCon was incredible! A huge thanks to @fperez_org, @odewahn, & all the organizers. I feel lucky to have been a part of it!”
—Rachel Thomas‏
JupyterCon is the best conference I've been to in my short career. Great job to everyone involved!”
—John Detlefs‏
JupyterCon was super well organized, the community is incredible and the speeches were awesome. Time well invested. Kudos to all.”—@rodsenra
An excellent gathering of people interested in open science and open source.”
—M. Tahir Ashraf, Masdar Institute
I loved the concentrated knowledge in one place. I’ll definitely come back next year if possible.”
—Sabrina Feder, Data Science Consultant
It was a wonderful conference. As a student, it was spectacular & really amazing to meet so many famous software personalities within 3 days. ”
—Ashutosh
The Jupyter community is exceptionally welcoming and diverse. JupyterCon provided a great environment for bringing more people into this community and a path forward filled with hope and optimism. I think this community is a great place to be if you want to make a positive impact in the world today.”
This was a great way to connect with other people doing awesome things with Jupyter. ”
—Adam Thornton, LSST

Program Chairs

Fernando Perez
is an assistant professor in Statistics at UC Berkeley and a Faculty Scientist in the Department of Data Science and Technology at Lawrence Berkeley National Laboratory. After completing a PhD in particle physics at the University of Colorado at Boulder, his postdoctoral research in applied mathematics centered on the development of fast algorithms for the solution of partial differential equations in multiple dimensions. Today, 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 co-founded its successor, Project Jupyter. The Jupyter team collaborates openly to create the next generation of tools for human-driven computational exploration, data analysis, scientific insight and education.

He is a National Academy of Science Kavli Frontiers of Science Fellow and a Senior Fellow and founding co-investigator of the Berkeley Institute for Data Science. He is a co-founder of the NumFOCUS Foundation, and a member of the Python Software Foundation. He is the recipient of the 2012 Award for the Advancement of Free Software from the Free Software Foundation.

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 has 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.

Committee members

Safia Abdalla (Interact/Project Jupyter/PyData)

Safia Abdalla (Interact/Project Jupyter/PyData)

Safia Abdalla is one of the maintainers of "nteract":https://nteract.io/, 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":http://chicago.pydata.org/. In her free time, she enjoys running, working out, and drinking tea.

Doug Blank (Bryn Mawr)

Doug Blank (Bryn Mawr)

Doug is an associate professor of computer science at Bryn Mawr College, an all-women's college outside of Philadelphia, PA. He has been using Python in education for 20 years, and Jupyter since its creation. He has developed many languages and tools for Jupyter specifically for pedagogy. His research area is in combining artificial neural networks and robotics in order to give robots self-motivation.

Brett Cannon (Microsoft)

Brett Cannon (Microsoft)

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

Shreyas Cholia (Lawrence Berkley National Laboratory)

Shreyas Cholia (Lawrence Berkley National Laboratory)

Shreyas Cholia leads the Usable Software Systems Group at Lawrence Berkeley National Laboratory (LBNL), focused 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 graduated from Rice University, where he studied Computer Science and Cognitive Sciences.

Rowan Cockett (University of British Columbia)

Rowan Cockett (University of British Columbia)

I am interested in the intersection of education, industry, and academia, and seeing what happens when you make powerful scientific modelling, visualization and communication tools accessible through the web. To explore these ideas, I founded 3point Science where we build web-based visualization software for the geoscience industry (Steno3D). 3point Science was acquired by Aranz Geo in 2016, and I have remained on as the CTO.

Sylvain Corlay (QuantStack)

Sylvain Corlay (QuantStack)

Sylvain Corlay is a quant researcher specializing in stochastic analysis and optimal control. He holds a PhD in applied mathematics from University Paris VI. 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. Besides Jupyter, Sylvain is a contributor to a number of other open-source projects for scientific computing and data visualization, such as bqplot, pythreejs and ipyleaflet. Sylvain also coauthored the xtensor C++ tensor algebra library. Sylvain founded QuantStack in September 2016. Prior to founding QuantStack, Sylvain was a quant researcher at Bloomberg LP and an adjunct faculty member at Columbia University and NYU.

Matt Davis (Clover)

Matt Davis (Clover)

Engineering manager and scientific Python user.

Catherine Devlin (Independent)

Catherine Devlin (Python programmer for 18F)

Catherine is an Innovation Specialist at 18F, a startup within the U.S. government that helps build and buy government software with open-source technology and modern development practices. She served as PyOhio’s founding chair, teaches introductions to programming and common FOSS topics, and is president of the Dayton Dynamic Languages user group. She is a frequent speaker at PyCon, PyOhio, and Ohio LinuxFest, and others. She lives in the woods near Dayton, Ohio with her wife and three horses.

Brian Granger (Jupyter/CalPoly)

Brian Granger (Jupyter/CalPoly)

Brian Granger is an associate professor of physics and data science at Cal Poly State University in San Luis Obispo, CA. He 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. Brian is a board member of the NumFOCUS Foundation and a faculty fellow of the Cal Poly Center for Innovation and Entrepreneurship.

Jason Grout (Bloomberg)

Jason Grout (Bloomberg)

Jason Grout recently joined Bloomberg LP. He has been contributing to the open source Sage mathematical software system since 2007 and until recently led the development effort and ran the Sage online notebook and the Sage cell server for several years. For the last several years, Jason has been contributing to IPython, including many contributions to the widget infrastructure. Previously, Jason was a postdoc at Iowa State University and an assistant professor of mathematics at Drake University in Des Moines, Iowa. He holds a PhD in mathematics from Brigham Young University.

Jess Hamrick (UC Berkeley)

Jess Hamrick (UC Berkeley)

Jess is a Ph.D. candidate at UC Berkeley studying how people use imagination to solve problems and reason about the world, and applying those ideas to machine learning and artificial intelligence. Previously, she completed her B.S. and M.Eng. in Computer Science at MIT. 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.

Lindsey Heagy (University of British Columbia)

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Lindsey Heagy is a PhD candidate at the University of British Columbia studying numerical geophysics. Her work focusses 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 core contributor to SimPEG, an open source framework for geophysical simulation and inversions.

Daniela Huppenkoten (New York University)

Daniela Huppenkoten (New York University)

I am a researcher in astrostatistics, where I work on Bayesian hierarchical models and machine learning methods to help us understand how stars explode, how black holes and neutron star forms and how we can use them to explore fundamental physics.

Kyle Kelley (Netflix)

Kyle Kelley (Netflix)

Kyle Kelley was a software developer at Rackspace 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.

Paco Nathan (O'Reilly Media)

Paco Nathan (O'Reilly Media)

Paco Nathan leads the Learning Group at O'Reilly Media. Known as a "player/coach" data scientist, Paco led innovative data teams building ML apps at scale for several years and more recently was evangelist for Apache Spark, Apache Mesos, and Cascading. Paco has expertise in instructional design, machine learning, distributed systems, functional programming, and cloud computing with 30+ years of tech-industry experience, ranging from Bell Labs to early-stage startups. Paco has advised Amplify Partners and GalvanizeU and was cited in 2015 as one of the Top 30 People in Big Data and Analytics by Innovation Enterprise. He is the author of Just Enough Math, Intro to Apache Spark, and Enterprise Data Workflows with Cascading.

Peter Parente (MaxPoint Interactive)

Peter Parente (MaxPoint Interactive)

Peter Parente is a computational engineer at MaxPoint Interactive where he focuses on improving the user experience for a team data scientists. He combines and contributes to open source as part of this work, with a particular focus on Project Jupyter. Prior to joining MaxPoint, Peter was a member of the IBM Emerging Technology team for ten years and received his doctorate in computer science at UNC-Chapel Hill.

Ana Ruvalcaba (CalPoly San Luis Obispo)

Ana Ruvalcaba (CalPoly San Luis Obispo)

Ana is Marketing & Operations Manager for Project Jupyter. In this role she oversees projects that relate to Jupyter’s events, marketing and operations. Ana is a graduate of California Polytechnic State University, San Luis Obispo where she earned a Business Administration degree in 2002.

Steven Silvester (Continuum)

Steven Silvester (Continuum)

Steven is a Software Engineer who served 10 years in the US Air Force prior to joining Continuum Analytics in 2015. He started working on project Jupyter in 2013 by absorbing the Octave magic into Oct2Py, and has since written kernels for Octave, Matlab, and Scilab. He is working full time on JupyterLab, the next generation user interface for the Jupyter Notebook.

Becky Sweger (Independent)

Becky Sweger (18F)

Becky works at the intersection of people and data. As a software and data engineer at 18F, a digital consultancy inside the United States government, she supports the U.S. Department of the Treasury as Senior Technical Lead on the DATA Act team. This team standardizes U.S. federal spending data, making it meaningful and accessible to lawmakers, industry, press, and the public. Previously she was the Director of Data and Technology at National Priorities Project, a federal budget research organization. A twenty year tech veteran, she’s held leadership positions in fields ranging from higher education to healthcare.

Tracy Teal (Data Carpentry)

Tracy Teal (Data Carpentry)

Tracy Teal is a co-founder and the Executive Director of Data Carpentry. She received her PhD in Computation and Neural Systems from California Institute of Technology and was an NSF Postdoctoral Researcher in Biological Informatics. She worked at Michigan State University as a Research Specialist with the Institute for Cyber-Enabled Research and then as an Assistant Professor in Microbiology. While an assistant professor, she saw researchers' need for effective data skills to effectively and reproducibly conduct research, and co-founded Data Carpentry to scale data training along with data production. She is involved in the open source software and reproducible research communities, including as an Editor at the Journal for Open Source Software.

Kristen Thyng (Texas A&M)

Kristen Thyng (Texas A&M)

Kristen is in the Oceanography department, doing research on physical oceanography using numerical models to simulate flows. She also uses modeling to study tidal energy, where turbines are placed in areas of fast-moving water to generate electricity. She teaches Python for the Geosciences using Jupyter notebooks hosted through JupyterHub, with nbgrader for the grading system.

Jamie Whitacre (UC Berkeley)

Jamie Whitacre (UC Berkeley)

Jamie Whitacre is the Technical Project Manager for Project Jupyter. She works with the core Jupyter team on development strategy and in strengthening connections with the larger Jupyter community. She works from the Berkeley Institute for Data Science (BIDS) and is an affiliate of the Lawrence Berkeley National Laboratory. Jamie has extensive experience designing and building scientific data systems for genomics, medical, and biodiversity research initiatives.

Carol Willing (CalPoly San Luis Obispo)

Carol Willing (CalPoly San Luis Obispo)

Carol Willing is a Director of the Python Software Foundation, a Jupyter Steering Council member, and a Geek in Residence at "FabLab San Diego" where she teaches wearable electronics and software development

Advisory committee

  • Josh Bloom (Berkeley)
  • Hugo Browne-Anderson (Datacamp)
  • Greg Caporaso (Northern Arizona Univ.)
  • Tim Clem (Github)
  • Kevin Fleming (Bloomberg)
  • Dan Gisolfi (IBM)
  • Ben Hamner (Kaggle)
  • Katy Huff (UIUC)
  • Eric Jones (Enthought)
  • Meredith Lee (Berkeley)
  • Ali Marami (RBrain)
  • Jessica McKellar (Dropbox)
  • Julia Meinwald (TwoSigma)
  • Cleve Moler (Mathworks)
  • Shahrokh Mortazavi (Microsoft)
  • Travis Oliphant (Continuum)
  • Jack Parmer (Plotly)
  • Alberto Pepe (Authorea)
  • Monica Rogati (Insight Data Science)
  • Arfon Smith (StSci)
  • Julie Steele (Silicon Valley Data Science)
  • William Stein (SageMathCloud)
  • Andy Terrel (NumFOCUS)
  • Matt Turk (UIUC)
  • Natalie Villalobos (Google)
  • Chris Wiggins (Columbia/NYT)
  • Owen Zhang (DataRobot)