JupyterCon 2023

A Goodman


  • Alyssa Goodman Keynote
Afshin Darian

Afshin Darian is a technical director at QuantStack. He is a member of the Jupyter Notebook, JupyterLab, and Jupyter Server councils. Darian is a co-author of JupyterLab and currently works on several layers of the Jupyter stack.

  • State of the Union: Jupyter Community
Alejandro Coca-Castro

Hola, I'm Alejandro (he/him) ⭐

  • đŸ§Ș Research Fellow at the Alan Turing Institute, UK's national institute for data science and artificial intelligence. My fellowship research focuses on the development of software for the intelligent fusion of environmental and climate data.

  • 🌎 Lead of the Environmental Data Science book, a computational notebook community for Open Environmental Science.

  • đŸ‘„ Core member of The Turing Way and scivision, and also an active member of the Pangeo Europe community meetings.

  • 🎓 Mentee and mentor in Open Science projects through the Open Life Science programme.

  • 👀 Topic editor at the Journal of Open Source Education (JOSE).

  • Environmental Data Science Book: A Computational Notebook Community for Open Environmental Science
Aleksandra PƂoƄska

Startup manager, lawyer, passionate about graphics, co-founder of mljar

  • Share Jupyter Notebook as a web app with Mercury framework
Alexander Goscinski

My name is Alexander Goscinski, I am currently pursuing a PhD which is reaching its end at the École Polytechnique FĂ©dĂ©rale de Lausanne (EPFL) in Materials Science and Engineering in the Laboratory of Computational Science and Modeling. My research focuses on studying features of machine learning models used for the prediction of atomistic properties. This allows us to better understand the internals of these kinds of models and thereby inspiring new developments. I am passionate about developing software that helps researchers to push the boundaries of materials science research. In my free time, I enjoy tennis and running outdoors. In addition to my research, I am also skilled in programming languages such as Python and C and am interested in diving more into Rust and Scala. I have experience managing high-performance computing systems and have contributed to several open-source software projects in the field of computational materials science. I am always looking for opportunities to collaborate with others and learn from their experiences.

You can contact me alexander.goscinski[at]epfl.ch

  • Scicode-widgets: A toolkit to bring computational thinking into the classroom
Allan Wasega

Allan Wasega is a budding technical writer and researcher based in Nairobi, Kenya. A recent Computer Science graduate, Allan has served as a technical writer with Tingle Software, a Nairobi-based software company where he has been helping to create user and technical documentation. As one of the 64 accepted interns in the December 2022 cohort of Outreachy interns, Allan has been working on restructuring JupyterHub’s documentation using the Diataxis framework. Since 2019, Allan has also been a mentor at KamiLimu, a structured mentorship program for students pursuing technology-aligned courses in institutions of higher learning in Kenya. Besides mentorship and writing, Allan loves reading books and listening to podcasts, especially those that touch on philosophy, uncertainty, and risk. Connect further with Allan on twitter: @alwasega.

  • Restructuring and Improving JupyterHub Documentation Using the DiĂĄtaxis Framework: Experience and Lessons
Alyssa Goodman

Alyssa Goodman is the Robert Wheeler Willson Professor of Applied Astronomy at Harvard University and a Research Associate of the Smithsonian Institution. Her research and teaching interests span astronomy, data visualization, prediction, and online systems for research and education.

  • Alyssa Goodman Keynote
Amit Rathi

Amit is a software developer & the founder of ReviewNB, a code review tool for Jupyter Notebooks.

He's a Carnegie Mellon graduate, previously worked at Amazon Music team in Seattle & helped build location stack at HyperTrack.

Amit is a strong proponent of automated testing & code reviews as they help us quickly build reliable software & learn from each other. He's deeply interested in the human side of software engineering- development processes, collaboration tools, and such.

  • Building GitHub Code Review Experience for Jupyter Notebooks
  • Simplify DevOps with Executable Notebooks
Ana Ruvalcaba

Ana Ruvalcaba is a founding member of the Jupyter Executive Council and is Director of Project Jupyter’s presence at California Polytechnic State University. She holds a Bachelor of Science degree in Business Administration with a minor in Ethnic Studies. Ana’s areas of expertise include program/project management, people management, operations, budgeting, and global events. Over the years she has collaborated with a wide variety of stakeholders in open source, tech, and university environments to deliver a unique set of contributions.

  • State of the Union: Jupyter Community
Andrii Ieroshenko
  • Introducing Jupyter Scheduler: Native support in Jupyter for running and scheduling Jupyter notebooks as jobs
Anne Fouilloux

Open Science and FAIR Software and Data Advocate.

Focus on strengthening the Nordic position within climate modeling by leveraging, reinforcing and complementing ongoing national, European and world-wide initiatives. Interested in emerging technologies and passionate about bridging skills between different sets of expertise.

  • Environmental Data Science Book: A Computational Notebook Community for Open Environmental Science
Antoine Blanchard

Antoine is a senior consultant at Datactivist, a French cooperative and participatory company whose mission is to open data and make them used and useful. Operating at all steps of data opening and reuse, Datactivist works with both data producers and data re-users. He advises research organizations and funders that engage with open science and open their research data.

Antoine was trained in agricultural sciences as well as science and technology studies (STS). Since 2005, he has worked at the crossroads of public engagement with science and digital tools for Café des sciences, DeuxiÚme labo, University of Bordeaux, and Datactivist. His main achievements include the French network of science bloggers; the Manifesto for an emancipating, self-critical and responsible scientific mediation; the first Science Hack Day organized in France; activism for open data on research funding; the award-winning Hacketafac student digital innovation contest; and a report for the INOS Erasmus+ project on open innovation activities in higher education.

  • How to convince French HSS researchers to use Jupyter Notebooks ? Autopsy of a missed attempt
Balaji Alwar

Balaji Alwar is working with Berkeley Research, Teaching, and Learning and Computing, Data Science and Society to design and scale the Berkeley DataHub, a service that provides interactive computing environments to educators and students across campus using open source tools in the Jupyter ecosystem and beyond. He has a bachelor's degree in computer science and graduated with a master's degree in education technology from Harvard. Previously, he was a product lead for a research project focused on upskilling at the Harvard Kennedy School. He is passionate about using technology for public goods that offer immersive and equitable learning experiences.

  • Supporting new pedagogical approaches in Education using Jupyter Hubs at Berkeley
BenoĂźt Bovy

BenoĂźt Bovy is a freelance scientific software developer and musician. He has a background in geoscience (geography, geology) and is a regular contributor to the Python scientific / PyData stack (Xarray). He is also active in the Belgian music band Roscoe.

  • Ipytone: Interactive Audio in Jupyter
  • Ipytone: Interactive Audio in Jupyter
Brian Granger

Brian Granger is a co-founder of Project Jupyter.

  • Introducing Jupyter Scheduler: Native support in Jupyter for running and scheduling Jupyter notebooks as jobs
Carlos Cordoba

I'm the Spyder lead maintainer, a role I've been doing for almost ten years now. I'm also part of the Jupyter Kernels council. During the last four years I worked at Quansight, leading a team that maintained Spyder, and before that at Anaconda for three years, creating packages for the Anaconda distribution and also working with a small team to improve Spyder.

  • The Spyder debugger: An interactive debugger based on Jupyter technologies
Carlos Herrero

Carlos is a Scientific software developer passionate about AI and its applications to robotics.

Prior to QuantStack, he worked as an intern at Instituto AI2, developing algorithms for 3-D printing with 6-axis robots.

His current work focuses on expanding the Jupyter ecosystem by contributing to JupyterLab and voila and developing new extensions to integrate ROS in JupyterLab.

  • Visual Programming in JupyterLab with Blockly
  • Real Time Collaboration in Jupyter
Cheuk Ting Ho

After having a career in data science, Cheuk now brings her knowledge of data and passion for the tech community as the developer advocate for Anaconda. Cheuk constantly contributes to the open-source community by giving free talks and tutorials and organising sprints to encourage diverse contributions.

  • Driving down the Memray lane - Profiling your data science work
Christopher Pyles

Christopher Pyles is a software engineer who graduated from the University of California, Berkeley after studying computer science and data science. He started working on Otter-Grader, an autograding library for Python and R that is compatible with Jupyter notebooks, while studying at UC Berkeley and continues to be its primary maintainer. He currently works as a software engineer in web development.

  • Otter-Grader: A Lightweight Solution for Creating and Grading Jupyter Notebook Assignments
Colin Brown

Second year PhD student at Northern Illinois University.

  • Understanding and Visualizing Dependencies between Notebook Cells
Cory Gwin
  • GitHub Keynote
Craig Peters

Craig is a Staff Product Manager at GitHub, focused on making coding accessible through developer tools. He has contributed extensively to Apache Hadoop, Open Stack, and Kubernetes. He enjoys cycling, cooking, and hiking with family.

  • GitHub Keynote
CĂ©cile Hardebolle

Cécile Hardebolle is a teaching advisor and learning scientist at the Center for Digital Education of Ecole polytechnique fédérale de Lausanne (EPFL). Originally trained as an engineer, she holds a PhD in Computer Science. She was formerly a researcher and lecturer in Computer Science at a French grande école (CentraleSupélec, Paris) and she has taught in several French engineering institutions. At EPFL, Cécile accompanies teachers on innovation projects for teaching and learning in science and engineering disciplines, with a focus on digital and ethical skills. She has developed several workshops on the use of notebooks for teaching sciences and engineering as well as the Jupyter for Education website of EPFL (https://go.epfl.ch/notebooks).

  • Jupyter notebooks for education: Computational thinking in practice
DamiĂĄn Avila

Father, Software Developer, Quant, (formerly) Biochemist, and some other things ;-) Currently living between Córdoba and Buenos Aires, Argentina. I have made some contributions to popular Open Source projects such as Jupyter, Nikola, and Bokeh. I have also started several projects being RISE (a “live” slideshow for the Jupyter notebook) the most popular one. You can easily find videos of some of my talks and tutorials at multiples national and international conferences. How can I help?

  • No Magic Added - Deploying Multiple JupyterHubs to Multiple Clouds from one Repository
Daniel Goldfarb

Daniel is an engineer at Bloomberg L.P. with experience developing Trading Systems, Risk Analytics, and applications for Financial Analysis of Equities and Fixed Income securities. He holds a Ph.D. in Molecular Biophysics from the University of Virginia, and was a CFA charter holder and member of the Chartered Financial Analyst Institute for more than 10 years. He is the Open Source maintainer of Matplotlib's MPLFINANCE package (https://pypi.org/project/mplfinance/), and the author of McGraw-Hill's "Biophysics Demystified."

  • Why Won't My Favorite Notebook Extension Work in JupyterLab?
Daniel Mietchen

A biophysicist interested in integrating open research and education workflows with the web.

ORCID: https://orcid.org/0000-0001-9488-1870

Scholia: https://scholia.toolforge.org/author/Q20895785

The work presented here is the result of an ongoing collaboration with Sheeba Samuel.

  • Computational reproducibility of Jupyter notebooks from biomedical publications
David Beniamine


  • TĂ©tras Lab : an open source platform propulsing notebooks as Web applications
David Brochart

Jupyter core developer.

  • Jupyter Server—the workhorse that drives nearly all Jupyter web applications
  • Real Time Collaboration in Jupyter
David Koop

David Koop is an Assistant Professor in the Department of Computer Science at Northern Illinois University. His research interests include data visualization, reproducibility, and computational notebooks. A focus of his research is on methods that support users in data exploration, analysis, and visualization tasks to they can focus on important ideas and decisions. He received his Ph.D. in Computing from the University of Utah in 2012.

  • Notebook Archaeology: What does an .ipynb file (not) tell us?
David Qiu

SDE II at AWS, focused on building Jupyter AI. Previously studied physical computational chemistry at UIUC. @dlqqq on GitHub.

  • Jupyter AI: Bringing Generative AI to Jupyter
  • Introducing Jupyter Scheduler: Native support in Jupyter for running and scheduling Jupyter notebooks as jobs
David Rouquet

I have a Phd in computer science and my research interests are around Natural Language Processing and Semantic Web.
Since 2015 we started TĂ©tras Libre (https://tetras-libre.fr), an IT consulting, research and development firm, based in Grenoble (France), and structured by the Open Source principles. There I conduct data science, software and research projects.

  • TĂ©tras Lab : an open source platform propulsing notebooks as Web applications
David Stirling

David Stirling is a data scientist at Glencoe Software. He specialises in producing image analysis workflows and tooling to assist researchers in quantifying and exploring image-based data. He is also interested in integrating popular open source tools with the OMERO ecosystem to provide user-friendly connectivity between packages. David previously worked in the Cimini Lab within the Broad Institute of MIT and Harvard, where he contributed to the CellProfiler image analysis software package. He also produced popular plugins which allow users to make use of powerful AI packages such as Cellpose and StarDist from within this software.

Emil Rozbicki is the Head of Applications for Glencoe Software. He is an expert in bioimage data management, visualisation, and analysis at scale. Emil is a physicist by training, prior to joining Glencoe he worked at University of Dundee investigating mechanisms underlying early-stage avian embryo development. During this time, he designed and built the first light sheet microscope in the UK and built analysis routines for investigation of cell behavior at the full organism scale during early-stage development. Currently he is focused on building solutions for the management and analysis of large scale bioimage datasets especially in high content and multiplexed imaging domains for some of the largest academic and biopharma organizations in the world.

  • Synchronizing the data science workflow with data management at scale
Denisa Checiu

Hello, I am Robotics Software Developer at QuantStack. I'm also currently in my third year, pursuing a bachelor’s degree in Robotics and Intelligent Systems with a minor in Computer Science, in Germany. My interests also include Machine Learning, AI and Computer Vision.

  • Visual Programming in JupyterLab with Blockly
Dhavide Aruliah

Dr. Dhavide Aruliah is the Director of Education at Quansight LLC. He holds BSc & MSc degrees in Mathematics from Simon Fraser University & a PhD. in Computer Science from the University of British Columbia. After completing postdoctoral work at the Fields Institute for Research in Mathematical Sciences and Western University, he served as a professor in the Faculty of Science at Ontario Tech University. In 2015, he left his academic career to work as Director of Training at Anaconda, Inc. and later as an independent consultant. His principal area of research is scientific computing, specifically in computational inverse problems. He is more broadly interested in numerical linear algebra, partial differential equations, optimization, scientific software development, and in high-performance computing.

  • 10 Years of Teaching with Jupyter: Reflections from Industry & Academia
Diego Torres Quintanilla

I am an engineering manager at Two Sigma. My team is responsible for the most basic functionality of our internal market research platform: virtual environment management, source control, (... other things) and Jupyter!

  • How JupyterLab 4 is strategic to Two Sigma (and you)
Diogo Castro

Diogo Castro is a full stack software engineer, currently working in the storage group of the CERN IT department. He has been contributing to CERN's Jupyter based, Service for Web-based ANalysis (SWAN), since he joined CERN in 2017 and, more recently, contributed to CERNBox, CERN's sync and share service, and AFS, a distributed filesystem used by CERN researchers.

  • Federated collaborative workflows for Jupyter
Eduardo Blancas

Eduardo Blancas is the Co-Founder and CEO of Ploomber, a Y Combinator-backed company developing tools to bridge the gap between interactive data work and production. Before that, he was a Data Scientist at Fidelity Investments, where he deployed the first customer-facing Machine Learning model for asset management. Eduardo holds an M.S. in Data Science from Columbia University and a B.S. in Mechatronics Engineering from TecnolĂłgico de Monterrey.

  • Beyond Papermill: A New Notebook Executor For Running Notebooks in Production
Edward Comyn-Platt

I am currently an analyst for the Copernicus Climate Change Service (C3S) Climate Data Store (CDS) and have a history working in land surface modelling and earth observation. I am driven by the objective that we should all be able to have access to, and have the tools to amke use of, the data outputs from climate models and satellite observations. Historically, this has been the role of specialists, however as the world becomes significantly more computer literate we can make huge bounds in progress by enabling access to a wider audience.

The C3S is an EU project which aims to provides information to support adaptation and mitigation policies in response to a changing climate. The CDS is the vehicle for ensuring that the data products and tools created by specialists within C3S are made accessible and discoverable to a wider audience of users.

  • Using Jupyter-notebooks to document and support climate and meteorology data
Emilien Schultz

Social scientist, sociology of science and health, postdoctoral researcher at médialab, Sciences Po. See more at : http://eschultz.fr/

  • How to convince French HSS researchers to use Jupyter Notebooks ? Autopsy of a missed attempt
Eric Charles

Eric Charles is committer for Jupyter Notebook, Jupyter Server and JupyterLab. He has founded Datalayer to make it easier for data analysts and developers to build what they need on top of the Jupyter ecosystem.

  • The past, present and future of the Jupyter Notebook
Eric Gentry

Open source developer of Mesh Align Plus and contributor to Jupyter, software engineer, raspberry pi tinkerer, tech/green-energy/sci-fi enthusiast, photographer...

  • The past, present and future of the Jupyter Notebook
Erik Sundell

Erik is a distinguished Jupyter contributor and maintainer of projects in the JupyterHub github organization, especially interested in deployments of JupyterHub in Kubernetes.

  • What's new and exciting in JupyterHub
Federico Fierli

Federico Fierli is an EUMETSAT sicence specialist since 2019 as expert in atmospheric dynamics and chemistry and communicate and teach on many aspects of satellite data and applications to a wide range of users.

Since 2002 he is Senior Scientist at National Research Council, Italy (now on-leave) and Associate Professor of Climate Physics, University of Rome. PhD at Paris University and then European Space Agency Fellowship.

His science background is on atmospheric and climate science with a focus in on the coupling between the composition and circulation of the atmosphere and its climatic impact. Federico was leader Scientist in many projects including in-situ campaigns and educational programs

  • Jupyter for Copernicus - improve the use of Earth Observation data
Fernando PĂ©rez

Fernando PĂ©rez (@fperez@fosstodon.org) is an Associate Professor in Statistics at UC Berkeley and scientist at LBNL. He builds open source tools for humans to use computers as companions in thinking and collaboration, mostly in the scientific Python ecosystem (IPython, Jupyter & friends). A computational physicist by training, his research interests include questions at the nexus of software and geoscience, seeking to build the computational and data ecosystem to tackle problems like climate change with collaborative, open, reproducible, and extensible scientific practices. He is a co-founder of Project Jupyter, the 2i2c.org initiative, the Eric and Wendy Schmidt Center for Data Science and Environment at Berkeley, the Berkeley Institute for Data Science and the NumFOCUS Foundation. He is a recipient of the 2017 ACM Software System Award and the 2012 FSF Award for the Advancement of Free Software.

  • Two decades of IPython and Jupyter - strategy, community and technical thoughts for the road ahead.
  • State of the Union: Jupyter Community
Florian Wetschoreck

Sr. Software Engineer at Databricks. Co-Creator of bamboolib, ppscore, pyforest.

  • Building on Jupyter at Databricks
Fons van der Plas

Working on Pluto.jl, a beginner-friendly notebook environment for Julia! Very excited to get to know you better. đŸŒ»

  • Pluto.jl – reactive and reproducible notebooks for Julia
Forrest Bao
  • CodePod: Scalable Computational Notebook on a Hierarchical Whiteboard with Scoped Runtime
Frederic Collonval
  • What’s New in JupyterLab 4.0
Gabriel Fouasnon

Gabriel Fouasnon is a frontend caterpillar (10 years experience) morphing into a web accessibility butterfly (1 year in the making). He works at Quansight Labs under a grant from the Chan Zuckerberg Initiative’s Essential Open Source Software for Science program to improve accessibility in the Jupyter ecosystem. (Follow along at jupyter-a11y.netlify.app!) This is his first conference talk.

  • WAAAT! Accessibility Testing JupyterLab
Gabriela Vives

Gabriela is a User Experience Researcher and Designer working at QuantStack, passionate about working in scientific domains and contributing to the Jupyter Project. She first graduated with master degrees in nuclear energy and cognitive science. After working for research, she decided to continue her studies and graduated in Human-Computer Interactions. Prior to QuantStack, Gabriela worked as a User Experience Designer at Schlumberger for 4 years, conducting user research and creating user-centered interfaces for geoscience software.

  • The UX of computational thinking
Gayle Ollington


  • JupyterCon 2023 Reception
Georgiana Dolocan

Georgiana Dolocan is an Open Source Infrastructure Engineer at 2i2c and a JupyterHub team member.
Georgiana cares about building inclusive communities and open work practices. She served in the JupyterHub Contributor in Residence role, after getting involved with the community though an Outreachy internship. She has now switched roles and mentored an Outreachy intern, using her own experience in this position to grow the community.
You can follow Georgiana's work on GitHub at @GeorgianaElena.

  • Reusable JupyterHub Pytest Plugin
  • No Magic Added - Deploying Multiple JupyterHubs to Multiple Clouds from one Repository
Giuseppe Angelo Porcelli

Principal Machine Learning Solutions Architect at Amazon Web Services (AWS)

  • Boost productivity with generative AI and scalable development using Jupyter Notebooks from anywhere
Greg Michaelson

Bio: Greg Michaelson is Cofounder and Chief Product Officer at Zerve, a young, stealthy startup that’s rethinking the data science development experience. Previously, Greg was an early joiner at DataRobot where he played many roles, including Chief Customer Officer. Prior to that, he worked as a data scientist in the financial sector after earning a PhD in applied statistics from the University of Alabama. In his spare time, Greg also manufactures a line of flavored breakfast cereal toppings called Cerup. He lives in Spring Creek, Nevada with his wife, four children, and two Clumber Spaniels.

  • AutoML as it should have always been
Guillaume Lemaitre
  • Predictive survival analysis and competing risk modeling with scikit-learn, scikit-survival, lifelines, Ibis, and DuckDB (Part 1)
  • Predictive survival analysis and competing risk modeling with scikit-learn, scikit-survival, lifelines, Ibis, and DuckDB (Part 2)
Guillaume Plique

Guillaume Plique is a research engineer working for SciencesPo médialab in Paris.

He assists social sciences researchers with their various projects and help them regarding methodology, data collection and build customized tools to meet their needs.

He also develops and maintains some of the lab's numerous Open Source tools and libraries.

  • Visual Network Analysis from the comfort of your Jupyter notebook
Hagsoo Kim
  • Per-cell Remote Execution on Jupyter
Hamel Husain

Hamel is currently an entrepreneur-in-residence at fast.ai working on nbdev. Hamel has built ML infrastructure and deployed data products at Airbnb, GitHub, and DataRobot. Hamel also contributes to many open-source projects related to machine learning infrastructure and developer tools.

You can find more about Hamel on his website.

  • Write, Document, Test and Distribute Python Packages With Jupyter & Quarto
Hans Fangohr

Hans Fangohr is a computational scientist and open source advocate. He is
heading the scientific support unit Computational Science at the Max Planck
Institute for Structure and Dynamics of Matter in Hamburg, Germany, and is
Professor of Computational Modelling at the University of Southampton in the
United Kingdom. He is working on research software engineering, including high
performance computing, data analysis and appropriate software engineering
methods in computational science.

He has created a number of open source scientific simulation and data analysis
packages, in particular in the area of micromagnetic modelling. To support the
effective use of computational methods for scientific research, Hans has
authored an Introduction to Python for Computational
for the training of engineers and scientists.

Further details are available on his homepage, blog, GitHub page and Mastodon handle https://fosstodon.org/@ProfCompMod .

  • Reproducible workflows with Jupyter: case study in materials simulation research
Hendrik Makait

Hendrik Makait is a data and software engineer building systems at the intersection of large-scale data management and machine learning. Currently, he works as an Open Source Engineer at Coiled improving Dask and its distributed execution engine.

  • Dask and Distributed Computing
Hooncheol Shin

A software engineer who does something meaningful
Work at MakinaRocks where we develop MLOps products called "Link" and "Runway"

I'm eager to enable machine learning to have a real-world impact.

GitHub: https://github.com/hunhoon21

  • The easiest way to collaborate on Jupyter
  • A Case of Developing a Jupyter Extension: its challenges and our solutions
  • Per-cell Remote Execution on Jupyter
Hwiyeon Cho
  • GitHub
  • Per-cell Remote Execution on Jupyter
J.J. Allaire

J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE. J.J. is an author of several packages in the R Markdown publishing ecosystem including rmarkdown, flexdashboard, learnr, and distill, and also worked extensively on the R interfaces to Python and TensorFlow. J.J. is now leading the Quarto project, which is a new Jupyter-based scientific and technical publishing system.

  • Jupyter Notebooks + Quarto for customizable and reproducible documents, websites and books
  • Write, Document, Test and Distribute Python Packages With Jupyter & Quarto
Jack Fitzsimons

Jack leads the technology development at Oblivious, a Dublin-based technology startup focused on privacy-enhancing technologies. He holds a DPhil from the University of Oxford, and has worked on a wide range of data-centric challenges in industry; from topics in computer vision at NASA's Jet Propulsion Laboratory to quantitative data analysis at ElectroRoute, the European energy trading subsidiary of Mitsubishi. Jack has been an active member of the UN's Privacy-Preserving Technologies Task Team since 2020 and the UN PET Lab since its inception.

  • Eyes-off data science: a transparently opaque framework for data processing
Jake Diamond-Reivich

Jake is one of the creators of the Mito Python package. Mito is a spreadsheet inside Jupyter that writes the equivalent Python for each edit. He started working on Mito with his twin brother and best friend from college when they all graduated from the University of Pennsylvania together in 2020. He received a bachelor's in finance, which he has not used once -- since he is now building open source software :)

Jake has helped some of the largest companies in the world implement Jupyter and bring spreadsheet users into the Jupyter environment.

  • How to Bring Spreadsheet Users to Jupyter
James Colliander

James Colliander is a Professor of Mathematics at the University of British Columbia. He is a Co-Founder of the International Interactive Computing Collaboration (2i2c.org), Co-Founder of the education technology company Crowdmark, and Co-Founder of Callysto. While serving as Director of the Pacific Institute for the Mathematical Sciences (PIMS) during 2016-2021 and in partnership with Compute Canada and Cybera, he helped establish Canada's national scale JupyterHub service Syzygy.

  • Accelerating Discovery for NASA Cryosphere Communities with JupyterHub
James Stix

Based within the University of Edinburgh’s centre for digital expertise, EDINA, managing the design, development and rollout of an innovative service called Noteable, based upon computational notebook platforms and capabilities for teaching and learning applications and developing the commercialisation process pipeline.
Noteable provides tailored, accessible, organised package environments for teachers and learners to fully realise the potential of digital notebook platforms for digital innovation, data analysis, machine learning, statistical modelling and more.

  • Jupyter for education with Noteable
James Varndell

I am a Scientific Software Engineer at the European Centre for Medium Range Weather Forecasts, working on open-source scientific Python for climate data discovery, analysis and visualisation.

  • Using Jupyter-notebooks to document and support climate and meteorology data
Jan-Hendrik MĂŒller

Jan-Hendrik has a background in Biophysics and is passionate about open source tools used in scientific research and science communication.
While creating code-generated animations of physics phenomena during his studies, he began to contribute to sci-vis-python packages and initiated the project jupyter-compare-view. His goal is to to make the scipy ecosystem more accessible by improving documentation tools.

  • Plywood Gallery - a new framework to generate python documentation via notebooks
Jason Grout

Jason is an open-source Jupyter developer and community leader and staff software engineer at Databricks. In Jupyter, Jason has worked on Jupyter Widgets, JupyterLab/Jupyter Notebook, and many other parts of the Jupyter ecosystem. At Databricks, he works on the Databricks Notebook platform. Previously, Jason was a software engineer at Bloomberg, taught mathematics at Drake University in Des Moines, Iowa, and contributed to the open-source SageMath software system.

  • Building on Jupyter at Databricks
Jason Grout

Jason Grout is a staff software engineer at Databricks working on interactive computational interfaces. In Jupyter, Jason helped build JupyterLab and ipywidgets and has contributed to many other parts of the project.

  • State of the Union: Jupyter Community
Jason Weill

Jason Weill is a Senior Front-End Engineer at Amazon Web Services; a contributor to JupyterLab, Jupyter Governance, and Jupyter Scheduler; and a member of the JupyterLab Council, the Jupyter Security Working Group, and the Jupyter Diversity, Equity, and Inclusion Standing Committee. Public statements by Jason represent his opinions alone and not necessarily those of Amazon or any of its subsidiaries.

  • Introducing Jupyter Scheduler: Native support in Jupyter for running and scheduling Jupyter notebooks as jobs
Jenn kotler

Jenn Kotler is the user experience designer at the Mikulski Archive for Space Telescopes where she designs data search and analysis tools for telescope missions including Webb, Hubble, TESS, and Kepler, all available for free use. Her design goal is to make data easily accessible so everyone can do amazing science. She lives in a historic row house with her partner, creaking wood floors, a clawfoot bathtub, and a menagerie of mammals

  • Notebooks for All: Accessibility & Jupyter Notebooks
  • Astronomy Notebooks for All: A Project to Develop More Accessible Jupyter Notebooks
Jeremy Tuloup

Jeremy Tuloup is a Technical Director at QuantStack and a Jupyter Distinguished Contributor. Maintainer and contributor of JupyterLab, JupyterLite, Jupyter Notebook, VoilĂ  Dashboards, and many projects within the Jupyter ecosystem.

  • Creating interactive Jupyter websites with JupyterLite
  • Navigating the Jupyter Landscape
  • The past, present and future of the Jupyter Notebook
Joe Lucas

Joe Lucas is a Senior Security Researcher for Artificial Intelligence on the NVIDIA AI Red Team. He was formerly a member of the AWS Red Team and a member of US Cyber Command. He is passionate about machine learning security education and helped architect the DEFCON 30 AI Village Capture-The-Flag competition. He has previously spoken at PyCon US, PyData Global, and HushCon.

  • Post-exploitation in Jupyter Environments
Johan Euphrosine

Developer Relations Engineer @Google, playing with "Open Source Silicon".

  • Accelerating the Open Source Silicon Ecosystem with Jupyter Notebooks
Johan Mabille

Johan Mabille is a Technical Director specialized in high-performance computing in C++. He holds master's degree in computer science from Centrale-Supelec.

As an open source developer, Johan coauthored xtensor, xeus, and xsimd. He is also involved in the development of mamba. Johan is also active in frontend projects, he participated to the development of the debugger in JupyterLab and recently made the migration to CodeMirror 6.

Prior to joining QuantStack, Johan was a quant developer at HSBC.

  • Navigating the Jupyter Landscape
  • Xeus kernels in the browser
John M. Shea

John M. Shea is a Professor of electrical and computer engineering at the University of Florida. His research is in the areas of wireless communications and networking, with emphasis on military communications, software-defined radio, networked autonomous systems, and security and privacy in communications. He teaches classes related to wireless communications, stochastic methods, and data science.

  • Tools for Interactive Education Experiences in Jupyter Notebooks and Jupyter Books
Jongseob Jeon
  • Accelerate your ML Cycle from Model development to deployment using Jupyter (feat. Extension Link)
Jongsun Shinn

Machine Learning Engineer at Makinarocks (2019.04 ~)

  • Accelerate your ML Cycle from Model development to deployment using Jupyter (feat. Extension Link)
Jose Montero

I hold a BSc + MSc in Physics from Salamanca University (Spain) and a MSc + PhD in Physics from Complutense University of Madrid (Spain), the latter obtained under the supervision of Dr. JosĂ© Herrero Rueda and Dr. Cecilia GuillĂ©n Arqueros (CIEMAT). After several years doing research in energy-related institutes -- CIEMAT (Spain) and IFE (Norway) -- now I work as a Researcher at the Ångström Laboratory, Uppsala University (Sweden). My research efforts can be framed within a green-nanotechnology perspective, i.e., I am interested in the use of nanotechnology for minimizing the impact of human activity on the environment. In addition, I am involved in developing teaching and learning activities with a focus on Education for Sustainable Development (often using Jupyter).

Contact José: https://www.katalog.uu.se/profile/?id=N13-1041

  • Good Practices, Missed Opportunities and the use of Jupyter notebooks for Inquiry-based Learning
Jovan Stojanovic

I am currently working as a Software Engineer at Inria Saclay, in the Soda team, that focuses on research around data science and machine learning applied to health and society.
I am also a maintainer of the dirty-cat package, an open-source Python tool that facilitates machine learning on dirty data.
I worked previously as a data scientist for Eurostat and the OECD, two international organizations.

  • Machine learning with dirty tables: encoding, joining and deduplicating
Julia Wagemann

I am an independent consultant, educator and community-builder who works across strategy, user engagement and training of Big Earth Data and Emerging Technologies. My work is in the intersection between data providers and users aiming to make large volumes of Earth data better accessible and used. For the past four years, I have trained more than 2000 Earth Observation and climate practitioners.

I have been working with Jupyter notebooks since 2014 and have developed more than 100 educational workflows on topics such as access and analysis of large volumes of Earth data and Machine Learning.

Previously, I worked for the European Space Agency and the European Centre for Medium-Range Weather Forecasts.

  • Jupyter for Copernicus - improve the use of Earth Observation data
  • Five guiding principles to make Jupyter Notebooks educational and reusable
Justin Eldridge
  • Otter-Grader: A Lightweight Solution for Creating and Grading Jupyter Notebook Assignments

associate professor at Université Claude Bernard Lyon 1
co-head of a scientific information and communication training unit

  • How to convince French HSS researchers to use Jupyter Notebooks ? Autopsy of a missed attempt
Lee Quick

Branch Manager for Data Analysis Tools @ Space Telescope Science Institute, Data Management Division.

  • Space Telescope Science Institute Notebook ecosystem
Lisa Yan
  • Otter-Grader: A Lightweight Solution for Creating and Grading Jupyter Notebook Assignments
LoĂŻc EstĂšve

LoĂŻc has a background in Particle Physics, which is how he discovered Python towards the end of his PhD. After a few year stint in an investment fund of writing mostly C++ and as much Python as possible,
he was lured back to an academic environment at Inria.

He is a scikit-learn and joblib core contributor and has been involved in a number of Python open-source projects in the past 10 years, amongst which Pyodide, dask-jobqueue, sphinx-gallery and nilearn.

  • Leveraging the Jupyter ecosystem to create and run the "Machine Learning in Python with scikit-learn" massive open online course
Luciano Resende

Luciano Resende is an AI Platform Architect at Apple AI/ML organization and a Jupyter Distinguished Contributor. Luciano's expertise is in open source, and enterprise-grade AI platform technologies with about 20 years of experience successfully designing, building, and delivering complex software in fortune 500 companies and open source. He has a strong background in open source big data platforms such as Apache Spark, and data science building blocks such as the Jupyter Notebook Stack, Elyra and Apache Toree Scala kernel.

  • Elyra an AI development workspace based on Jupyter Notebooks
Luis Lopez

Luis Lopez is a Research Software Engineer at the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado. He has helped develop tools and services to facilitate data access and discoverability across different NASA Earth science missions. He is a passionate advocate of open science and has contributed to open source projects such as Apache Nutch and ipyleaflet. He’s always happy to help scientists find ways to make their workflows simpler. Luis has presented his work at SciPy LATAM and the IEEE annual Big Data symposium.

  • ITS_LIVE: Jupyter and cloud native formats to map climate change.
Maarten Breddels

Maarten Breddels is an entrepreneur and freelance developer/consultant/data scientist working mostly with Python, C++ and Javascript in the Jupyter ecosystem. Creator of Solara, ipyvolume and Vaex, founder of Vaex.io and Widgetti. His expertise ranges from fast numerical computation, API design, to 3d visualization. He has a Bachelor in ICT, a Master and PhD in Astronomy, likes to code and solve problems.

  • IPywidgets: From an experiment in the Notebook to Production-ready data app
Manon Marchand

All time user of notebooks, I'm curently an software engineer at the Strasbourg astronomical Data Center where we actively develop and participate in open science.

  • Sharing notebooks onto the European Open Science Cloud
Marc Buffat

I am professor at the mechanical engineering department of the university, Lyon1 with expertise in Computational Fluid Dynamics. Fed on Linux since my university studies, I am an ardent supporter of free software.

For my teaching activities, I have been using Python for more than 10 years as well as the Jupyter environment and Jupyter notebook, to develop a more interactive pedagogy using “Learning By Doing”, both for undergraduate students in classical mechanism and for graduate student in fluids mechanism and numerical method: examples on my professional website (in french)

  • Flexible course management and validation system using Jupyterhub with additional services using Flask
Marcin Sieprawski

Experienced System Architect and R&D Project Manager with 20+ years of enterprise software design and development. Founder and leader of Big Data Lab in Software Mind. He is now involved in CS3MESH4EOSC project (https://cs3mesh4eosc.eu/), leading tasks on Reference cloud interoperability platform and distributed Data Science environments.

He developed Big Data solutions before it became mainstream. In the years 2005-2008 he was involved in development of technology for the first web-scale Semantic Web startup: garlik.com, his team started using Hadoop in February 2006, as one of the first companies in the world.

He participated in and lead many commercial projects which included Big Data, high volume and high velocity solutions, in various sectors. He was a Work Package leader and provided Big Data architecture in in a number of EU-funded research projects.

Connect: https://www.linkedin.com/in/marcinsieprawski/

  • Federated collaborative workflows for Jupyter
Marco Gorelli

Marco is a pandas core developer working at Quansight. He has authored several code quality tools (cython-lint, absolufy-imports, auto-walrus, and nbQA). His background is in mathematics and data science.

  • nbQA- run any standard Python code quality tool on a Jupyter Notebook
Maria TeleƄczuk

Maria TeleƄczuk, PhD, is a Data Scientist at Owkin and a PyLadies Paris Organiser. She is a firm believer in an open-source and advocate for good coding practices. She enjoys participating in initiatives which aim to empower people of various origins, ages and backgrounds.

  • Getting Started With Python
  • Getting Started With Python
Marianne Corvellec

Marianne Corvellec is a core developer of scikit-image, a popular Python library for scientific image processing, where she specializes in biomedical applications. Her technical interests include data science workflows, data visualization, and best practices from testing to documenting. She holds a PhD in statistical physics from École normale supĂ©rieure de Lyon, France. Since 2013, she has been a regular speaker and contributor in the Python, Carpentries, and FLOSS communities.

  • Getting Started With Python
  • Getting Started With Python
Marine Gosselin

Marine is a Developer Advocate at Taipy. She has 5+ years as Data Scientist

  • Skills: Machine Learning techniques, Python, Rule-based models & AI
  • Strong Experience in Predictive and Descriptive Analytics, Fraud detection
  • Master's Degree, Msc Big Data Analytics for Business, IÉSEG School of Management. Accounting & Finance, McGill University - Hong Kong University of Science and Technology, Business School
  • Taipy or how to build stunning Python Applications from your Jupyter Notebooks
Martha Cryan
  • What’s New in JupyterLab 4.0
Martin Grund

Martin is the engineering lead for Spark Connect in Apache Spark and Databricks Connect. He comes with a background in databases and query engines, but is now working on bringing the power of data science and machine learning with Apache Spark to all communities.

  • Use Spark from anywhere: A Spark client in Python powered by Spark Connect
Martin RENOU

Martin Renou is a Technical Director at QuantStack. Prior to joining QuantStack, Martin also worked as a Software Developer at Enthought. He studied at the French Aerospace Engineering School ISAE-Supaero, with a major in autonomous systems and programming.

As an open-source developer, Martin has worked on a variety of projects, such as ipygany (a 3-D mesh visualization library for the Jupyter Notebook) and ipympl (an interactive Matplotlib backend for Jupyter)

Passionate about 3-D rendering and computer graphics, Martin has also developed a 3-D Chess GUI based on OpenGL, and an interactive canvas library during his spare time.

Martin is the main author of xeus-python, he worked on xtensor and xsimd, and is now working on Jupyter interactive widgets.

Furthermore, Martin is a Jupyter Distinguished Contributor.

  • And VoilĂ !
Mathieu Morey

Data scientist, researcher (NLP) and senior consultant (open data).

  • How to convince French HSS researchers to use Jupyter Notebooks ? Autopsy of a missed attempt
Matthew Rocklin

Matthew is an open source software developer in the numeric Python ecosystem. He maintains several PyData libraries, but today focuses mostly on Dask a library for scalable computing. Matthew worked for Anaconda Inc for several years, then built out the Dask team at NVIDIA for RAPIDS, and most recently founded Coiled to improve Python's scalability with Dask for large organizations.

  • Dask and Distributed Computing
  • Distributed Data Science for Humans with Dask
Matthew Elliott

Matt is a PhD student in Biomolecular engineering at the University of California Santa Cruz, where he researches neuroscience and machine learning. Previously, he created a popular open-source Jupyter environment called io, which received 5 million downloads on Dockerhub. He also has a Youtube channel that teaches coding on Jupyter and received over half a million views. Matt is the lead engineer of WetAI, a Jupyter web portal that serves as an online laboratory for neuroscience and AI research. In his free time, Matt enjoys reading math texts and is an avid surfer.

  • Jupyter as a Brain-Computer-Interface
Maxime Liquet

Software Engineer at Anaconda, maintaining and improving the open-source data viz libraries of the HoloViz ecosystem. Previously a civil engineer specialized in flood risk assessment, making flood maps with hydraulic simulation software.

  • Interactive data exploration in a notebook with hvPlot
Meag Doherty

As a Sustainable Software advocate and Experience Strategy leader, Meag Doherty is committed to building programs and communities that empower people and drive positive change in technology and society.

Since 2019, Meag has been leading user experience strategy at the All of Us Research Program at the National Institutes of Health and, most recently, serving as the Deputy Chief User Experience Officer.

In addition to her professional experience, Meag is a Fellow at the Software Sustainability Institute and has worked with notable organizations like the Mozilla Foundation, the U.S. House of Representatives, and MassGeneral Brigham.

Meag holds a Bachelor of Science from Providence College and is constantly seeking opportunities to learn and grow, both within the realm of technology and beyond.

  • Maximizing the Impact of User Feedback: Effective Practices for Community Management
Merve Noyan

I'm a developer advocacy engineer working at Hugging Face, building tools to enable reproducibility, transparency and robustness in taking machine learning models to production. I'm also a graduate researcher working on natural language processing.

  • Taking notebooks to production using Hugging Face
Milana Vuckovic

Meteorologist, former weather forecaster, now data analyst passionate about data visualisation and jupyter notebooks.

  • Using Jupyter ecosystem for more accessible open weather forecast data
  • Bridging the gap between climate data and policy makers: The CLIMAAX project example
Min Ragan-Kelley

Min is a senior research engineer at Simula Research Laboratory in Oslo, Norway, supporting open source open science and education. He is a member of the JupyterHub team and the JupyterHub team representative on the Jupyter Software Steering Council, and the original author of JupyterHub.

Min has been contributing to Jupyter projects since 2006, starting with IPython Parallel as a physics undergraduate student with Brian Granger.

  • What's new and exciting in JupyterHub
Mohammad Wasil

Mohammad Wasil is a research associate and PhD student at Hochschule Bonn-Rhein-Sieg, Germany. he works on the project e2x where the main goal is to provide constructive alignment in education. His role in the project is to build an infrastructure for teaching, examination, and machine learning research in general.

  • e2xgrader: An Add-on for Improved Grading and Teaching with Jupyter Notebooks at Scale
  • e2xhub: Simplifying Course Setup and Management in Education with JupyterHub at Scale
Nate Rush

Hiya, I'm Nate! I'm the CTO at Mito (https://trymito.io), where we've been building an open-source spreadsheet extension for Jupyter for the past two years, with the goal of reducing the barriers to entry for new Python programmers. I'm passionate about supporting OSS, building a healthy startup ecosystem within the Jupyter community, and rich outputs cells!

  • De-Regid the Widget: Making Jupyter a Haven for Startups
Nicolas Chauvat

Free software and Python developer since the mid-90s, Founder and CEO of Logilab since 2000, former co-organizer of the very first EuroPython and EuroSciPy events. Semantic web expert and functional languages enthusiast.

  • JupyterApps a platform to develop, deploy and share single-page web applications from jupyter notebooks
Nicolas Poulain

Capytale project leader

  • Capytale: a case of large-scale use of jupyter notebooks in education

Researcher in Metocean engineering
Short bio: https://annuaire.ifremer.fr/cv/23466/en/

  • Notebooks to support the growth of sea-based renewal energy sector
Olivier Grisel

Olivier is a software engineer at Inria and work as a maintainer for the scikit-learn project, a popular open source machine learning library for Python. Olivier also teaches applied Deep Learning and Machine Learning at UBS Vannes.

  • mastodon: https://sigmoid.social/@ogrisel
  • github: https://github.com/ogrisel
  • twitter (RIP): https://twitter.com/ogrisel
  • Predictive survival analysis and competing risk modeling with scikit-learn, scikit-survival, lifelines, Ibis, and DuckDB (Part 1)
  • Predictive survival analysis and competing risk modeling with scikit-learn, scikit-survival, lifelines, Ibis, and DuckDB (Part 2)
Omer Dunay
  • Autoreload in Production at Meta
Omer Dunay

A Software Engineer at Meta, Ex Microsoft, excited about notebooks, language services and everything related to making developing Python.
Linkedin - https://www.linkedin.com/in/omer-dunay-505a9544/
Would love to chat on:
1. Notebook Product in enterprise environment.
2. Python Language Services (An Example for a language server I wrote https://developers.facebook.com/blog/post/2022/07/18/enabling-faster-python-authoring-with-wasabi/)
3. GenAI for notebooks - How GPT-4 alike can be leveraged for notebooks.
4. Supporting ML tools through notebooks.
5. Any other topic that comes to mind!

  • Autoreload in Production at Meta
Parul Gupta

Parul Gupta is a Production Engineer with data science and interactive computing. Her focus lies in building infrastructure to increase dev efficiency - persistence and reliability of interactive notebooks and supporting R infrastructure at Meta. She graduated from University of Massachusetts Amherst with Master’s degree in computer science.

She aspires to help bridge the gaps across the genders in the field of technology. She has also mentored aspiring female students and computer science enthusiasts in various early career programs – most recently, mentored with non-profit organization, ‘Rewriting the code’.
Her tech work outside of Meta also reflects the same vision as she is a proud contributor of Fairlearn, an open-source project to help data scientists improve fairness of AI systems.

In her free time, she enjoys dancing, painting and traveling.

  • A tale of notebook recovery: session reconnects, execution recoveries and more
Patrick Jermann

After studies in Geneva (TECFA) and Pittsburgh (LRDC) I joined EPFL in 2003 to coordinate eLearning projects and conduct research in the field of Computer Supported Collaborative Learning (CSCL). Since 2013, I lead the Center for Digital Education (CEDE) where we do MOOCs, Jupyter Notebooks, Campus Analytics, etc.

  • Jupyter notebooks for education: Computational thinking in practice
Patrick Smyth

Patrick Smyth is Chief Learner at Iota, an organization focused on accessible technical training, consulting, and infrastructure development. From 2019 to 2021, Patrick coordinated Columbia's Foundations for Research Computing, a program dedicated to building expertise and community around research computing at the university. Patrick is a blind researcher, developer, and entrepreneur who thinks critically about how infrastructure can create—or lower—barriers to entry in STEM research. In 2022-2023, Iota is working with Space Telescope Science Institute, the center that performs science operations for the Hubble and James Webb space telescopes, on Astronomy Notebooks for All, an initiative to make web-based scientific outputs more accessible to people with disabilities. Patrick is a Fulbright Fellow (Berlin, 2010) and received his PhD from The Graduate Center, CUNY.

  • Notebooks for All: Accessibility & Jupyter Notebooks
  • Astronomy Notebooks for All: A Project to Develop More Accessible Jupyter Notebooks
Paul Plöger
  • e2xgrader: An Add-on for Improved Grading and Teaching with Jupyter Notebooks at Scale
Paul Romer

Paul Romer, a University Professor at NYU, was co-recipient of the 2018 Nobel Prize in Economics Sciences. His work lies in the intersection of economics, innovation, technology, and urbanization. The central conclusion is that there are many feasible ways to speed human progress.

Before coming to NYU, Paul taught at Stanford, and while there, started Aplia, an education technology company he later sold to Thomson Learning. Prior to Stanford, he taught at UC Berkeley, the University of Chicago, and the University of Rochester. He earned a Bachelor of Science in Mathematics and a Doctorate in Economics from the University of Chicago.

  • Paul Romer Keynote
Pavithra Eswaramoorthy

Pavithra is a Developer Advocate at Quansight, where she works to support the PyData community. She is also a part of the Bokeh core team and the Dask maintenance team. In her spare time, she enjoys a good book and hot coffee. :)

  • Community-first open source: An action plan!
Philipp Rudiger

A long timer at Anaconda Inc., Philipp Rudiger is a Staff Software Engineer developing open-source and client-specific solutions for data management, visualization and analysis. He is the author of the open source dashboarding and visualization libraries Panel, Lumen, hvPlot and GeoViews and one of the core developers of Bokeh, Datashader and HoloViews. Before making the switch to software development he completed a PhD and Masters in Computational Neuroscience at the University of Edinburgh working on biologically inspired, deep and recurrent neural network models of the visual system.

  • Rapidly prototyping and deploying powerful data applications in Jupyter using Panel and Lumen
Pierre-Olivier VallĂšs

Computer Scientist - DevOps at EPFL (École polytechnique fĂ©dĂ©rale de Lausanne)
In charge of the JupyterHub / JupyterLab service (technical)

  • Jupyter notebooks for education: Computational thinking in practice
Piotr PƂoƄski

Software engineer with a passion for creating Data Science tools, MLJAR co-founder.

  • Share Jupyter Notebook as a web app with Mercury framework
Piyush Jain
  • Jupyter AI: Bringing Generative AI to Jupyter
  • Introducing Jupyter Scheduler: Native support in Jupyter for running and scheduling Jupyter notebooks as jobs
Richard Nemeth

My name is Richard, I come from Slovakia and currently live in Denmark. I work for a company called Adamatics as a Senior ML Engineer.

With mathematical background, my career started off 8 years ago as a Data Scientist but very soon ventured into Data and Software Engineering, which finally combined into Machine Learning Engineering. I've worked in multiple different industries across multiple EU countries, gathering knowledge, tips, and tricks for many different aspects of engineering.

In the last 2 years, I've been mainly focusing on developing and maintaining applications in Kubernetes from data science and data engineering perspectives.

  • MLOps made easy and reproducible with Jupyter and containers
Rick Wagner

Rick Wagner is a Principal Research Systems Integration Engineer at UCSD. Rick began his career using cyberinfrastructure as a tool for research in astrophysics, working on problems in cosmology and supersonic turbulence. His research was largely done on campus, NSF, and DOE computing resources, the same kinds of systems he later managed for SDSC. Rick took a break from UCSD to work for Globus at the University of Chicago, helping researchers with data management solutions. Now Rick is part of the Research IT team, helping to design solution for projects that cut across the campus and beyond it. He is also trying to smooth the boundary between cybersecurity and research, and was a 2021 Trusted CI Fellow.

  • Security Tutorial/Discussion
Rosio Reyes

Rosio Reyes is a Software Engineer at Anaconda working as a part of the OSS Jupyter team. She is a Jupyter Notebook Council Member and contributes to the Notebook and NbClassic projects.

  • The past, present and future of the Jupyter Notebook
Rowan Cockett

Rowan is on the Executable Books team where he develops MyST Markdown (https://myst-tools.org) in the context of scientific writing. Rowan is also the CEO and cofounder of Curvenote, which is an interactive, online writing platform for science, engineering & research teams, with dedicated integrations to Jupyter. Rowan has a Ph.D. in computational geophysics from the University of British Columbia (UBC). While at UBC, Rowan helped start SimPEG, a large-scale simulation and parameter estimation package for geophysical processes (electromagnetics, fluid-flow, gravity, etc.), which is used in industry, national labs, and universities globally. He has won multiple awards for innovative dissemination of research and open-educational resources, including a geoscience modelling application, Visible Geology, that has been used by more than a million geoscience students to interactively explore conceptual geologic models.

  • MyST Markdown: Using notebooks in scientific publishing workflows
Sabrina H. Szeto

Sabrina Szeto is an independent geospatial consultant empowering organisations to use geospatial data and technology. Sabrina has developed Jupyter Notebooks and conducted user training on atmospheric composition datasets for EUMETSAT since 2021. She is also recognised as a Google Developer Expert for Earth Engine. Previously, she was a geospatial analyst at Yale University’s School of the Environment. She holds a masters degree in forestry from Yale University and a bachelors degree in Anthropology from Princeton University.

  • Five guiding principles to make Jupyter Notebooks educational and reusable
Sangwoo Shim

Sangwoo Shim is Chief Technology Officer (CTO) and co-founder at MakinaRocks. He focuses on developing Machine Learning infrastructure and overseeing Al projects and solutions for manufacturing.
Sangwoo has pursued his career in various quantitative areas including quantitative finance, equity trading, and data analysis in global companies. Upon completion of his Ph.D. in Chemical Physics at Harvard University, he joined Bank of America Merrill Lynch in New York as a quantitative analyst. He later worked as a quantitative portfolio manager at WorldQuant and Millennium Capital in Old Greenwich and Singapore. Prior to MakinaRocks, he worked in the Big Data Analysis Group at Samsung Electronics.
Sangwoo believes that his expertise in statistics, optimization, and software engineering will contribute to achieving MakinaRocks’s mission to innovate manufacturing through artificial intelligence.

  • From Jupyter to MLOps: Jupyter as a key integrator for MLOps
Sarah Di Loreto Pollet
  • Flexible course management and validation system using Jupyterhub with additional services using Flask
Sarah Gibson

Sarah Gibson is an Open Source Infrastructure Engineer at 2i2c, an open source contributor and advocate. She holds more than two years of experience as a Research Engineer at a national institute for data science and artificial intelligence, as well as holding a core contributor role in the open source projects Binder, JupyterHub, and the Turing Way. Sarah is passionate about working with domain experts to leverage cloud computing in order to accelerate cutting-edge, data-intensive research and disseminating the results in an open, reproducible and reusable manner. Sarah holds a Fellowship with the Software Sustainability Institute and advocates for best software practices in research. She is a member of the mybinder.org operating team and maintains infrastructure supporting a global community in sharing reproducible computational environments. She has also mentored projects through two cohorts of the Open Life Science programme, imparting lived experience of her skills participating and leading in open science projects.

  • Restructuring and Improving JupyterHub Documentation Using the DiĂĄtaxis Framework: Experience and Lessons
  • How to grow the JupyterHub community and improve its practices by mentoring Outreachy interns
  • No Magic Added - Deploying Multiple JupyterHubs to Multiple Clouds from one Repository
Sathish kumar Thangaraj

I'm a Front-end developer who is enthusiastic and passionate about making software. I have hands-on experience in a wide range of software, tools and programming languages. I take great care in the user experience, architecture, and code quality of the things I build.

Some of the technologies I enjoy working most include JavaScript, ReactJS, NodeJS, TypeScript, MongoDB, Firebase, Docker, Kubernetes, C#, .NET, C, X86 Assembly.

I'm a Microsoft Certified Technology Specialist (WCF developer)`

Besides my work I enjoy setting up scaled down distributed systems with Raspberry PI 4 cluster. I use this as my home lab to experiment with high availability and scalability scenarios. I love to dig into open source projects to understand the internals of the software that I use.

  • The “Share” button for Jupyter Notebooks - A generic service for publishing and sharing notebook files
Sheila Kahwai

Sheila Kahwai is a Python developer from Nairobi, Kenya. She began her tech journey back in 2014 when she started pursuing a Computer Science degree. Eight years later, in 2022, she rediscovered her passion for tech after joining a coding Bootcamp.

As a student, she knew contributing to open-source was important but she didn't know why and where to start. When she came across the Outreachy internship program, she discovered that some of the most important applications being used are made possible by contributors no different than her. And this is when her open-source journey with JupyterHub began.

When she is away from her computer, she enjoys watching documentaries, trying out new recipes, and attending music festivals with her friends.

Connect with Sheila on Twitter: @sheila_kahwai

  • Reusable JupyterHub Pytest Plugin
Shravan Achar

I love trying out new technologies and build exciting software. I currently work at Apple building Data Platform services for data engineers, analysts and scientists. Jupyter Notebooks and Kubernetes are my current interests

  • The “Share” button for Jupyter Notebooks - A generic service for publishing and sharing notebook files
Simon Chabot

Software engineer at Logilab


  • Notebooks to support the growth of sea-based renewal energy sector
Simone Mantovani
  • Five guiding principles to make Jupyter Notebooks educational and reusable
Steen Manniche

Steen is a partner, co-founder, and engineer at ADAMATICS, a data-analytics company that specializes in providing insightful and actionable data solutions to businesses.

With a background in computer science and engineering, Steen has played an integral role in the development and implementation of the company's innovative data-analytics platform, AdaLab.

Through his work, Steen remains committed to the company's mission of leveraging data to help businesses make informed decisions and looks forward to continuing to innovate in the ever-evolving field of data analytics.

Join Steen in exploring the dark corners of authentication in JupyterHub in his talk

  • Let the right one in: Custom Authentication in JupyterHub
Stephannie Jimenez Gacha

Hello there!

My name is Stephannie Jimenez and I'm a software developer currently working at Quansight. I enjoy working in open source projects and have a soft spot for pets.

  • Inclusive and accessible scientific computing in the Jupyter Ecosystem
Stephen Macke

Stephen Macke is an engineer at Databricks working on notebook technologies. He completed his PhD at the University of Illinois, Urbana-Champaign in 2020, and has been obsessing about reactivity and state management in notebooks for way too long.

  • IPyflow: Supercharging Jupyter with Dataflow-Awareness
Steve Purves

I am a scientific software developer, data scientist/researcher and software product developer rolled into one. A team member of the Executable Books project where I work on thebe and CTO and co-founder of Curvenote where we are building tools and infrastructure for [much] better scientific communication and publishing.

An (electronic) engineer by background (Newcastle University, UK), I specialized in signal processing, computer vision, data science and machine learning and spent 20+ years helping both research and industry scientists (a lot of earth and geoscientists, but also data scientists in healthcare, finance, manufacturing, even dentists) build software to solve highly technical and scientific problems. I build apps that worked with huge datasets, 3d visualization and GPU-based HPC for server, desktops and the web.

Now I'm applying all of my time and experience to building software that can help change how we communicate, re-use and build on scientific work for a better future.

  • Thebe - add Jupyter-based interactive computing to modern websites

Engineer at heart. Consultant by profession.

Working with data analytics, machine learning and E2E solution delivery since 2010. I have a background in computer science and a masters degree in computer security. Love seeing young professionals grow, enthusiastic about being a catalyst in their growth.

  • MLOps made easy and reproducible with Jupyter and containers
Sune Askjaer

I am a Partner & Principal Data Scientist at ADAMATICS. With a background in computational chemistry, I now work as a consultant in the field of data science. I have worked with clients from various industries, including pharmaceutical companies and banks, where we have helped implement machine-learning models in real-world applications.

At ADAMATICS I use my data analysis and machine learning expertise to help clients extract valuable insights from their data and lower the barrier for citizen data scientists to contribute their domain expertise.

  • MLOps made easy and reproducible with Jupyter and containers
Suraj Rampure

Suraj Rampure is a Lecturer in the Halıcıoğlu Data Science Institute at UC San Diego. In addition to teaching undergraduate courses on programming, statistical inference, and practical machine learning, he manages the data science senior capstone program.
Suraj graduated with BS and MS degrees in Electrical Engineering and Computer Sciences from UC Berkeley in 2020 and 2021, respectively. While at Berkeley, he helped create and teach courses in computer science and data science.

  • Otter-Grader: A Lightweight Solution for Creating and Grading Jupyter Notebook Assignments
Tania Allard

Tania is the Director of Quansight Labs, an organisation that builds and sustains community-driven open-source projects and initiatives.
She has been a long-term open-source user, contributor, advocate, and maintainer.

  • Community-first open source: An action plan!
Tasha Snow

I am research scientist working to better understand high latitude ocean and glacier change and how it will impact the planet. My current work focuses on how oceans interact with glaciers in Greenland and Antarctica, and I am developing new ways to apply satellite thermal infrared imagery to study these systems. I specialize in remote sensing, machine learning, and have extensive oceanographic and glaciological field experience. One of my most exciting projects at the moment is leading the CryoCloud cloud-computing project (cryointhecloud.com) to help usher NASA Cryosphere communities into the cloud and to help build open-source science infrastructure and community best practices.

  • Accelerating Discovery for NASA Cryosphere Communities with JupyterHub
Taylor Baird

I am a PhD student working in the domain of method development in atomic-scale simulation under the supervision of Dr. Sara Bonella at Centre Européen de Calcul Atomique et Moléculaire
(CECAM) in Lausanne, Switzerland. Lately, I have become increasingly involved in work on the OSSCAR project. In addition to research, I spend a significant portion of my time assisting with the teaching of a master-level class, "Computational methods in molecular quantum mechanics". This role has provided an excellent opportunity to brandish the Jupyter notebook-based lessons developed within OSSCAR to enhance teaching, and I'm excited to share the positive experiences I've had with the rest of the Jupyter community.

  • OSSCAR: leveraging interactive Jupyter notebooks to enhance teaching in the scientific domain
Thijs van der Plas

DPhil student at University of Oxford.

  • Reproducible figures for scientific publication
Thomas Boyer Chammard

Thomas Boyer Chammard is a Software Systems Engineer at NASA's Jet Propulsion Laboratory, in Pasadena, CA. Part of his role is to develop and maintain the Jupyter ecosystem that is available across the Laboratory, which is comprised of an internal JupyterHub, BinderHub, and other services like NBViewer and ReviewNB. He also advocates for Jupyter best practices, and promotes adoption of the Jupyter ecosystem as an engineering tool across the Lab.

Thomas holds a Master of Engineering in General Engineering from École Centrale de Lille, in Lille, France.

  • Sending Rovers to Mars with Jupyter

Computer Engineer at Université Lyon 1, France.
From physical servers to software development through system administration, I run, maintain and develop the JupyterHub platform funded by the Include project for Université Lyon 1 and INSA.

  • Flexible course management and validation system using Jupyterhub with additional services using Flask
Thorsten Beier
  • Xeus kernels in the browser
Tim Metzler

I work as a research associate at Hochschule Bonn-Rhein-Sieg, University of Applied Sciences with a focus on developing tools for E-Assessment and Natural Language Processing.

GitHub: @tmetzl

  • e2xgrader: An Add-on for Improved Grading and Teaching with Jupyter Notebooks at Scale
  • e2xhub: Simplifying Course Setup and Management in Education with JupyterHub at Scale
Tim Paine

I am a quantitative developer at Cubist Systematic Strategies and an adjunct professor in the Computer Science Department at Columbia University. My background is primarily in application development with a focus on streaming analytics. I have been involved in the formation of several corporate open source efforts, and am a proud member and maintainer of open source projects in the FINOS, JupyterLab, and Conda Forge organizations.

  • Visualizing live data pipelines in JupyterLab with ipydagred3
Trung Le

Le Duc Trung is a Scientific Software Developer at QuantStack. He holds a Ph.D. in computational mechanics from Université Pierre-et-Marie-Curie (France). Before joining QuantStack, Trung worked as a research engineer at Mines ParisTech, CADLM (now Hexagon), and Safran Group.

At QuantStack, he works on several projects within the Jupyter ecosystem, from main projects like JupyterLab, VoilĂ , and ipywidgets to Jupyter extensions and widgets.

Trung is the author of ipyflex (a WYSIWYG layout editor for Jupyter widgets) and jupyterview (a VTK data visualization extension for JupyterLab)

As a personal project, Trung co-founded cast2cloud.com, a web-based mechanical simulation application based on the Cast3M finite element solver.

  • And VoilĂ !
  • Real Time Collaboration in Jupyter
Tyler Erickson

Tyler is a freelance geospatial technologist focused on addressing global sustainability issues. Drawing from a diverse background in engineering, Earth science, and information technology, he works to accelerate the transition from research discoveries to operational systems.

Previously, Tyler led the developer relations team for Google Earth Engine, a cloud-based geospatial analysis platform.

A snow hydrologist by training, he has degrees in civil & environmental engineering and geography from Colorado State University, California Institute of Technology, Stanford, and the University of Colorado at Boulder.

Loves to bike.

  • Addressing global sustainabilty challenges with Jupyter and cloud-based geospatial data platforms
Vinay Kakade

Vinay is currently the Founder and CEO of Abhyasu.com, an ed-tech initiative to teach Python and AI to 10-14 year old kids. Previously, he architected ML Platform at Lyft, co-founded a startup that was acquired by Lyft, built AWS Elasticsearch and CloudSearch services, and built Amazon.com's product search engine.

Vinay holds MS in Computer Science from Stanford University, USA, and BE in Computer Engineering from the College of Engineering, Pune, India.

  • Simplify DevOps with Executable Notebooks
Vincent Gosselin

Over 30+ years as AI specialist with ILOG and IBM.
Designed/Modeled several major AI projects for customers such as Samsung, McDonald’s, Dassault Aviation, Carhartt, Toyota, TSMC, Disney, etc.
* Skills: Mathematical Modeling, Machine Learning, Time Series.
* Strong Experience in Manufacturing, Retail & Logistics industries.

Main Objective: “Help companies go beyond AI pilots and be successful in bringing AI to their end-users”.

Msc Comp. Science & AI, University Paris-Saclay.

  • Taipy or how to build stunning Python Applications from your Jupyter Notebooks
Vincent Maladiere

Machine Learning engineer @Inria and @APHP, working on survival analysis.

‱ github: github.com/Vincent-Maladiere
‱ blog: vincent-maladiere.github.io/

  • Predictive survival analysis and competing risk modeling with scikit-learn, scikit-survival, lifelines, Ibis, and DuckDB (Part 1)
  • Predictive survival analysis and competing risk modeling with scikit-learn, scikit-survival, lifelines, Ibis, and DuckDB (Part 2)
Wasim Lorgat

Wasim is a software engineer, data scientist, and a core developer of nbdev. Previously, Wasim held technical leadership positions in South African startups. At DataProphet, he led the development of machine learning techniques for reducing defects in manufacturing plants. And at Aerobotics, he led the team that built aerial drone computer vision systems to provide farmers with high-resolution crop data.

You can find out more about Wasim on his website.

  • Write, Document, Test and Distribute Python Packages With Jupyter & Quarto
Yongjin Shin
  • The easiest way to collaborate on Jupyter
Yuvi Panda

Co-founder at 2i2c.org. Ex Wikimedia, ex GNOME. On a motorcycle or watching star trek or texting someone when not on a computer. Death to accidental complexity.


  • Best practices for building docker images for use with a JupyterHub
  • No Magic Added - Deploying Multiple JupyterHubs to Multiple Clouds from one Repository
Zach Sailer

Zach Sailer is a Senior Software Engineer at Apple, where he is the Jupyter Open Source Champion. He is a Jupyter Distinguished Contributor and the Jupyter Server Steering Council Representative.

  • The “Share” button for Jupyter Notebooks - A generic service for publishing and sharing notebook files
  • Jupyter Server—the workhorse that drives nearly all Jupyter web applications
shane knapp

Shane Knapp

UC Berkeley Datahub Technical Lead



  • Supporting new pedagogical approaches in Education using Jupyter Hubs at Berkeley