A. T. Darian is a technical director at QuantStack and a member of the Jupyter Executive Council. As an open source developer, Darian is a co-creator of JupyterLab and a contributor to several other projects in the ecosystem.

Prior to joining QuantStack, Darian worked on open-source software at Two Sigma, Anaconda, Alfresco, and OpenGamma. He holds an MA in history (Medieval Europe) from the University of California, Berkeley and a BA in philosophy and in medieval studies from Rutgers University.

Alexis is a C++ Scientific Software Engineer at Quantstack.

Alonso Silva is currently a Researcher on Verifiable AI at Nokia Bell Labs in the Machine Learning and Systems Research Lab. He has previously worked at Safran in the Department of Mathematics and Temporal Data, in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, working with Professor Jean Walrand, at INRIA Paris Rocquencourt working with Dr. Philippe Jacquet and as a Research Consultant/Intern at Bell Labs Headquarters in Murray Hill, New Jersey, working with Dr. Iraj Saniee. He did his Ph.D. at INRIA Sophia-Antipolis under the direction of Dr. Eitan Altman. He obtained his Ph.D. degree in Physics from the École Supérieure d'Électricité in June 2010.

Anne Fouilloux is the CTO of LifeWatch ERIC, founder of VitenHub AS, and a research
software engineer with 25+ years of experience in scientific computing and open,
reproducible research. She works at the intersection of FAIR data, research-software engineering, and the open scientific-Python ecosystem — Pangeo, and Galaxy — with a focus on
reproducible Earth-system and biodiversity science. Her current work turns research claims
into FAIR, citable, machine-readable nanopublications, and builds tooling that helps
researchers run rigorous, reproducible replications. ORCID: 0000-0002-1784-2920

Anne-Marie Tousch is a freelance data and machine learning consultant based in Paris. She holds a PhD in computer vision and has spent over a decade building production machine learning systems at Criteo, Datadog and a couple startups. She teaches data visualization to Master's students.

A seasoned software engineer, working in both batch and real time, data intensive, python application.

I am a Principal Investigator in the Center of Experimental Rheumatology at University Hospital Zurich and University of Zurich. I taught statistics at Maastricht University from 2018 to 2025. I received my academic training at Stanford University from 2013 to 2018, and at Inria and University of Bern from 2008 to 2012.

I'm Deepa, a QA Developer at IBM with 4 years testing enterprise storage on Kubernetes and OpenShift. I work on OpenShift Data Foundation, specializing in Disaster Recovery across multi-cluster environments — deploying clusters, validating failovers, and debugging storage issues. Curiosity drives me to explore and experiment. I'm here to share what I've learned along the way.

Evangelos Papoutsellis holds a PhD in Mathematical Image Processing from the University of Cambridge. His background spans academic research in France and the UK, industrial R&D, and open-source scientific software development. His work focuses on mathematical optimisation for inverse problems and computational imaging, with applications in medical imaging and materials science.

Fernando created IPython and co-founded Project Jupyter, the open notebook that redefined how scientists communicate with computers. In an era when AI can generate code faster than we can read it, what it means to build tools that help people think, not just execute, has never mattered more.

PhD researcher with a background in computer science, currently a Marie Skłodowska-Curie fellow at Sorbonne Université (LIP6) and IFP Energies nouvelles. My work focuses on applied AI and machine learning, with particular interest in retrieval-augmented generation, knowledge graphs, large language models, and unsupervised deep learning.

Data science tech lead at intella.tech · Mathematician at heart · Open source enthusiast

I'm a ML software engineer at probabl, doing core development for skore. I studied math and computer science and did a research masters in applied maths.

With a career rooted in the rigors of General Relativity, I specialized in building robust, ethical, and scalable AI systems. I have several years of experiences contributing to the open-source community, having led the development of MAPIE, the reference library in conformal predictions. I now work on reliable and scalable evaluation of GenAI systems, and took the lead of GLIDE, a new open-source package implementing state-of-the-art semi-supervised inference techniques.

Software research engineer at CNES since 2016, I've worked in satellite ground segment development and related projects for about 20 years. I've specialized myself in big data processing, deploying and using Hadoop and Spark for scientific data processing first in 2012. I then joined the CNES computing center team and helped users develop processing chains at scale using Dask or Slurm. At this time, I became a member of Pangeo community and contributed to deploy Dask enabled Jupyterhub for huge geospatial data analysis. I'm working now in the Data Campus division at CNES, where I maintain a snow detection tool and I also try to help improving the Python ecosystem around satellite raster processing (Xarray related projects like EOReader) and visualization.

Gijs van den Dool is a Senior Geospatial Data Scientist and Earth Observation specialist working independently with startups and early-stage ventures. With extensive experience in insurance, environmental consulting, and climate risk, he brings a proven ability to translate complex spatial data into actionable intelligence to support smarter decisions.
His work focuses on applying machine learning and satellite data to translate Earth Observation into data insights for policy, risk management, and decision-making, with a strong emphasis on making emerging technologies accessible to user communities.
His current projects include using Earth Observation Foundation models to feed digital twin–enabled decision-support systems for urban heat island mitigation, designed to assist planners and policymakers. In parallel, his research interest lies in modelling wildfire risk at the wildland–urban interface, where climate impacts intersect with urban growth and infrastructure exposure.

I live and breathe libre open-access, open-source software. I'm excited about all the wonderful FOSS communities that welcome new scientists and developers on a daily basis. I'm a member of the R Foundation, the Bioconductor Technical Advisory Board, and the director of the R Consortium Infrastructure Steering Committee, and a maintainer of way too many R packages ;)

Formally, Associate Professor at University of California San Francisco (UCSF), United States. Co-director of the UCSF Scientific Software Core and the UCSF Open-Source Program Office (OSPO), member of the Computational Biology Core, Helen Diller Comprehensive Cancer Center (UCSF), and advisory, operational, and user-supporting member of several UCSF high-performance compute (HPC) environments.

GitHub: https://github.com/HenrikBengtsson/, https://github.com/futureverse/

İlhan Polat is a mechanical engineer and holds a PhD degree on control theory from TU Delft/TU Eindhoven about bilateral teleoperation for robotics. He has worked as a control engineer in different industrial positions as well as a researcher in academia. Recently he has been working in the IoT verticals such as mining equipment, rotating machinery maintenance and smart buildings.

Ines builds tools for AI and NLP: spaCy, the go-to open source library for natural language processing in Python; Prodigy, a modern annotation tool for machine learning; and Ellf, a virtual assistant for agentic NLP development. Her work sits exactly where open source meets the practical craft of shipping language technology.

Technical Director at QuantStack and Project Jupyter core developer and maintainer (JupyterLab, Jupyter Notebook, JupyterLite).

Johan Mabille is a Technical Director specialized in high-performance computing in C++. He holds a master's degree in computer science from Centrale-Supelec. As an open source developer, Johan coauthored xtensor , xeus , and xsimd.

He leads the C++ team at QuantStack, where he oversees the development and maintenance of mamba, sparrow, and the Jupyter Xeus project.

Johan has also made significant contributions to JupyterLab.

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

I am a core contributor to Pandas and Apache Arrow, and one of the maintainers of GeoPandas and Shapely. I did a PhD at Ghent University and VITO in air quality research, worked at the Paris-Saclay Center for Data Science and at Voltron Data contributing to Apache Arrow. I am a freelance open source software developer and teacher.

Joseph Barbier is a data consultant and open-source contributor based in France. At Yellow Sunflower, he helps teams build reproducible data workflows and better reporting tools. His work mainly revolves around Python, R, and Typst, with a strong interest in open-source tooling and data visualization.

I am a PhD student in Epidemiology and Biostatistics at the University of Zürich and the University Hospital Zürich within the (Reliable AI Group). My research focuses on reliable and uncertainty-aware AI methods for biomedicine.
I hold an MSc in Statistics from ETH Zürich, where my thesis focused on linear regression with known error distributions, and dual bachelor’s degrees in Applied Mathematics from Paris 1 Panthéon-Sorbonne University and in Social Sciences from Sciences Po Paris.
When I’m not coding in R, I’m usually embroidering or wandering through Swiss pastures looking for cows and statistical inspiration.

I’m Kritik Sachdeva, currently working as a Support Professional at IBM. I’ve been working with Ceph & OpenShift for the past 5 years, and since college I had a great interest in technologies like K8s, containers, and computer Vision.
Since then, I’ve enjoyed exploring how different technologies can be integrated to solve real-world problems. Over the last couple of years, I’ve had the opportunity to speak at various community events & these experiences had helped me grow both technically and personally.

I am a Data Scientist and Sociologist working at the Sovereign Tech Agency. My main project focuses on researching frameworks for evaluating the impact of public funding in open-source software. I’m interested in open data, feminism, and the human dynamics behind tech structures. In my free time, I enjoy practicing yoga and reading.

Lawrence Mitchell works at NVIDIA. His focus is on high-productivity, high-performance libraries for data analytics. He leads the technical design and implementation of the cuDF-accelerated Polars GPU engine. Prior to joining NVIDIA he was a lecturer in computer science and applied mathematics at the University of Durham with research interests in high performance simulation of continuum mechanics, structure-preserving numerical methods, and preconditioning techniques for coupled multiphysics problems. He was a founding co-lead and technical architect of the open source Firedrake project for finite element simulation.

I'm a core maintainer of SciPy and Pixi, and a member of the Consortium for Python Data API Standards. I recently finished a master's degree in Computer Science and Philosophy at the University of Oxford.

Mackenzie leads the Mathis Lab at EPFL and created DeepLabCut, open source pose estimation software now used across thousands of biology labs. A model case for how open tools reshape an entire research field.

Mamy is a cryptography engineer, deep learning engineer and has designed too many threadpools to count. He spends his time shipping any math-heavy research to production, optimizing it along the way to better use the actual hardware they run on.

Marcus Denker is a permanent researcher (CR1, with tenure) at INRIA Lille - Nord Europe. Before, he was a postdoc at the PLEIAD lab/DCC University of Chile and the Software Composition Group, University of Bern. His research focuses on reflection and meta-programming for dynamic languages. He is an active participant in the Squeak and Pharo open source communities for many years. Marcus Denker received a PhD in Computer Science from the University of Bern/Switzerland in 2008 and a Dipl.-Inform. (MSc) from the University of Karlsruhe/Germany in 2004

Head of Product Management at Probabl, Marie is also co-organizer of Women in Machine Learning and Data Science Paris.

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.

🥇 Jupyter Distinguished Contributor

PhD — Research Software Engineer at INRIA

Mickael Ide is a Machine Learning Engineer on the Unstructured Data Processing team at NVIDIA, focused on developing GPU-accelerated algorithms for vector search and machine learning.

Olivier Grisel is a machine learning engineer at Probabl and a contributor to the scikit-learn library.

I'm a CNRS researcher at LEGI (Université Grenoble Alpes, CNRS) studying geophysical and astrophysical turbulence, mostly with lab experiments and numerical simulations. I'm also passionate into how to program and calcul for science, in particular using Python and its ecosystem, and teaching about these subjects.

Data Scientist Delivery Lead at AgileLab (Consulting in Data for Enterprises), I am passionate about Open Source and Tech communities. Before AgileLab I worked for almost 9 years as a Data Scientist/Software Engineer in a product company for Supply Chain Planning and Optimization. Then I took a sabbatical where I went on a programming retreat (Recurse Center) and went all in on tech communities. I help organize the local Python Milan meetup and helped launch the PyData Milan meetup. I got the programming language bug thanks to an underdog programming language (Nim), this led me into Open Source (Nimib). I have a background as a mathematician and I did not complete a PhD in Math Applied to Climate Dynamics (that brought me to live two years in Paris).

Open source developer in AI and head of datasets at Hugging Face. Quentin has been working on open source projects to democratize AI with a focus on data loading and sharing since 2020. His work includes helping research communities and companies in AI for text, audio, image, video and robotics, and also working on compute and storage solutions for AI datasets at Hugging Face.

I am a research engineer at Inria, part of P16 and of the SODA research team. I am one of the maintainers of the skrub Python package. I hold a PhD in Computer Science and I am also interested in research on tabular learning and tabular foundational models.

Started as a physicist, worked as data scientist and engineer, got interested in data tooling and became an Apache Arrow and Parquet contributor, focusing on the C++ and lately Rust implementations. Would like to see numerical computation become more accessible in general purpose languages and frameworks.

Romain Clement is a software engineer with over a decade of experience spanning data engineering, applied mathematics, and machine learning. Since 2018, he’s worked as an independent consultant, helping data teams streamline and productionize their workflows, bringing software engineering best practices into data science, MLOps, and beyond.

He’s an active open-source contributor, with personal projects and community involvement in ecosystems like Datasette. A regular speaker since 2019 and co-organizer of the Grenoble Python Meetup, he enjoys sharing pragmatic tools and techniques that make data work actually work.

Find out more on romain-clement.net

I am the JupyterHub and Jupyter Book community manager. I also lead the ORMIR community (www.ormir.org). I authored the book "Learn Python with Jupyter-Develop computational thinking while learning coding" (www.learnpythonwithjupyter.com).

Simon Danisch is the creator of Makie.jl, Bonito.jl, GPUArrays.jl, and BonitoBook.jl. With a background in cognitive science and computer vision, he has spent the last decade building out Julia's visualization, interactive UI, and GPU computing ecosystem.

Tim is a Quantitative Developer at Cubist Systematic Strategies.

Tim Weiland is a PhD student in the Methods of Machine Learning group at the University of Tübingen, where he works on scalable probabilistic PDE solvers.
His research combines Bayesian inference, sparse linear algebra, and physics-informed priors to make uncertainty quantification practical for large-scale scientific computing problems.

Wolf built Mamba and then Pixi, redefining how scientific Python environments are built, shared, and reproduced. The entire open source data stack runs on top of package management, and Wolf has spent years making that foundation solid.

Yann works on security for the Jupyter project. He moved into open source recently, after 8 years in French software startups such as MakiPeople and Graneet.