Adrin Jalali

I'm a computer scientist / bioinformatician who has turned to be a core developer of scikit-learn and fairlearn, and work as a Machine Learning Engineer at Hugging Face. I'm also an organizer of PyData Berlin.

These days I mostly focus on aspects of machine learning and tools which help with creating more ethical and fair decision making systems. This trend has influenced me to work on fairlearn, and to work on aspects of scikit-learn which would help tools such as fairlearn to work more fluently with the package; and at Hugging Face, my focus is to enable the community of these libraries to be able to share their models more easily and be more open about their work.

  • scikit-learn and fairness, tools and challenges
Alejandro Saucedo

Alejandro is the Chief Scientist at the Institute for Ethical AI & Machine Learning, where he contributes to policy and industry standards on the responsible design, development and operation of AI, including the fields of explainability, GPU acceleration, ML security and other key machine learning research areas. Alejandro Saucedo is also Director of Engineering at Seldon Technologies, where he leads teams of machine learning engineers focused on the scalability and extensibility of machine learning deployment and monitoring products. With over 10 years of software development experience, Alejandro has held technical leadership positions across hyper-growth scale-ups and has a strong track record building cross-functional teams of software engineers. He is currently appointed as governing council Member-at-Large at the Association for Computing Machinery, and is currently the Chairperson of the GPU Acceleration Kompute Committee at the Linux Foundation.


  • Industrial Strength DALLE-E: Scaling Complex Large Text & Image Models
Alexander CS Hendorf

Alexander Hendorf is responsible for data and artificial intelligence at the digital excellence consultancy KÖNIGSWEG GmbH. Through his commitment as a speaker and chair of various international conferences, he is a proven expert in the field of data intelligence. He has many years of experience in the practical application, introduction and communication of data and AI-driven strategies and decision-making processes. He is a Python Software Foundation Fellow, likes to work in small dedicated teams and loves to work with and contribute to the Python and PyData community.

  • A Primer to Maintainable Code
Alon Nir

Senior data scientist at Spotify. Dismal scientist at heart.
Trying to be a bit better every day.
Overall a huge nerd.

  • Sliding into Causal Inference, with Python!
Andreas Steiner

After his original studies in medicine, an MSc in bio-electronics, and MD with the Swiss Tropical Health Institute, Andreas has been working at Google since 2015. His main focus there has been on machine learning using Tensorflow and data mining, development of internal tools for data analysis.

  • JAX and Flax: Function Transformations and Neural Networks
Arkadiusz Trawiński, PhD

Product Lead/Data Scientist in ING for 2 years. Mainly working on optimization of tech infrastructure. Graduated Computer Engineering and Physics. PhD in Hight Energy Physics.

  • Introduction to scikit-learn II
  • Introduction to scikit-learn I
Arturo Amor
  • Evaluating your machine learning models: beyond the basics
  • Introduction to scikit-learn II
  • Introduction to scikit-learn I
Cheuk Ting Ho

Before working in Developer Relations, Cheuk has been a Data Scientist in various companies which demands high numerical and programmatical skills, especially in Python. To follow her passion for the tech community, now Cheuk is the Developer Relations Lead at TerminusDB - an open-source graph database. Cheuk maintains its Python client and engages with its user community daily.

Besides her work, Cheuk enjoys talking about Python on personal streaming platform and podcasts. Cheuk has also been a speaker at Universities and various conferences. Besides speaking at conferences, Cheuk also organises events for developers. Conferences that Cheuk has organized include EuroPython (which she is a board member of), PyData Global and Pyjamas Conf. Believing in Tech Diversity and Inclusion, Cheuk constantly organizes workshops and mentored sprints for minority groups. In 2021, Cheuk has become a Python Software Foundation fellow.

  • Revolutionalise Data Visulization with PyScript
Christian Barz
  • PhD in Mathematics
  • worked as Analyst and Data Scientist
  • Mathematical Modelling and Optimization Expert @Palaimon GmbH (current)
  • Decision making under uncertainty
Davide Poggiali

Data Analyst at FAR Networks srl.
Former Post-Doc fellow at the PNC - Padova Neuroscience Center, Italy.
PhD in Neurosciences, with a Master's degree in Mathematics.

  • Real-time estimation of an heat pump I/O state with IoT data.
Ed Shee

Ed comes from a cloud computing background and is a strong believer in making deployments as easy as possible for developers. With an education in computational modelling and an enthusiasm for machine learning, Ed has blended his work in ML and cloud native computing together to cement himself firmly in the emerging field of MLOps. Organiser of Tech Ethics London and MLOps London, Ed is heavily involved in lots of developer communities and, thankfully, loves both beer and pizza.

  • Optimizing inference for state of the art python models
Emmanuelle Gouillart

Emmanuelle (Emma) Gouillart is a researcher and a scientific Python developer. She has a background in physics and materials science, and she has carried on scientific research and software development during the last years. She became a core contributor of Python’s popular image processing library scikit-image since a large part of her research relies on extracting quantitative data from image datasets. She has also made major contributions to the plotly data visualization package. She has been a co-organizer of the first Euroscipy conferences, and she enjoys very much discussing with Python users about image processing and visualization at conferences. Emma is the scientific director of Saint-Gobain Research Paris, the main R&D center of the industrial group Saint-Gobain, a world leader in materials and solutions for the construction sector.

  • Image processing with scikit-image
  • Interactive Image Annotation with plotly and Dash
Francesco Bonazzi

MSc. in physics from the University of Milano, Italy (2012).
Software engineer in the industry (2012-2015).
PhD researcher at the Max Planck Institute of Colloids and Interfaces, Potsdam, Germany (2015-2018).
Data scientist (2018-now).

  • Array expressions and symbolic gradients in SymPy
Gaël Varoquaux

Gaël Varoquaux is a research director working on data science and health at Inria (French Computer Science National research). His research focuses on using data and machine learning for scientific inference, with applications to health and social science, as well as developing tools that make it easier for non-specialists to use machine learning. He has been working going building easy-to-use open-source software in Python for above 15 years. He is a core developer of scikit-learn, joblib, Mayavi and nilearn, a nominated member of the PSF, and often teaches scientific computing with Python, eg as a creator of the scipy lecture notes.

  • Evaluating your machine learning models: beyond the basics
  • Machine learning with missing values
Geir Arne Hjelle
  • Introduction to pandas
Hristo Vrigazov

Machine Learning Engineer with an interest in robotics, natural language processing and computer vision.
Have worked on various projects, such as driver assistance systems, recommender systems, word sense disambiguation, and others.
Author of several small open source packages, and have made small contributions to open source projects, such as ANTLR and Tensorflow.

  • Memory maps to accelerate machine learning training
Iliya Zhechev

I finished a masters in AI from Sofia University a few years ago. In my free time, I like doing neural network art, reading about emergence and cellular automata, or playing guitar. When I'm not home you can find me skiing, climbing or hiking.
I also sometimes do youtube - Ил Ай.

  • Emergent structures in noisy channel message-passing
Jaime Rodríguez-Guerra

Jaime holds a PhD in Biotechnology and believes that packaging is one of the pillars for reproducible research. He became a conda enthusiast while working on molecular modelling frameworks and machine learning pipelines for drug design.

  • conda-forge: supporting the growth of the volunteer-driven, community-based packaging project
Jakob Wasserthal
  • Deep learning at the Radiology & Nuclear Medicine Clinic / University Hospital Basel
Jannis Leidel

Jannis Leidel, better known as "jezdez" in the Python community, has until recently been working at Mozilla as a staff software engineer on the Mozilla data platform team, maintaining part of Mozilla’s data infrastructure and tools and before that as a web developer on the Mozilla Developer Network (MDN) project that documents Open Web technologies. He now works on the conda team at Anaconda to help co-maintain the conda package manager.

As an avid contributor to Open Source projects, he's incredibly proud of the different communities he has become part of, whether it's the Python packaging ecosystem, the data science community, the Django project, the conda-forge project or the Jazzband collective. As director at the Python Software Foundation he works in the packaging working group, the finance committee and as co-communication chair.

Feel free to reach out to him via Twitter at @jezdez (DMs are open).

  • conda-forge: supporting the growth of the volunteer-driven, community-based packaging project
Jarrod Millman
  • [Maintainer Track] Scientific Python / SPECs
Jeremy Tuloup

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

  • Interactive Data Science in the browser with JupyterLite and Emscripten Forge
Jesper Dramsch

Jesper Dramsch works at the intersection of machine learning and physical, real-world data. Currently, they're working as a scientist for machine learning in numerical weather prediction at the coordinated organisation ECMWF.

Before, Jesper has worked on applied exploratory machine learning problems, e.g. satellites and Lidar imaging on trains, and defended a PhD in machine learning for geoscience. During the PhD, Jesper wrote multiple publications and often presented at workshops and conferences, eventually holding keynote presentations on the future of machine learning.

Moreover, they worked as consultant machine learning and Python educator in international companies and the UK government. Their courses on Skillshare have been watched over 25 days by over 2000 students. Additionally, they create educational notebooks on Kaggle, reaching rank 81 worldwide.

  • Increase citations, ease review & collaboration – Making machine learning in research reproducible
  • Increase citations, ease review & collaboration – Making machine learning in research reproducible
Joris Van den Bossche
  • Introduction to geospatial data analysis with GeoPandas
  • [Maintainers track] Interoperability in the DataFrame landscape: DataFrame API & PyArrow Update
Joshy Cyriac

Trained software engineer now doing machine learning/deep learning at the University Hospital Basel.

  • Deep learning at the Radiology & Nuclear Medicine Clinic / University Hospital Basel
Julien Jerphanion

I am mainly interested in computational, algorithmic and mathematical methods. I first started to contribute to open-source in 2017 and since then my contributions focused on scientific software.

Since April 2021, I work at Inria as a Research Software Engineer, mainly on improving scikit-learn's native performance. I became one of scikit-learn maintainers in October 2021.

  • Scaling scikit-learn: introducing new computational foundations
Katharine Jarmul

Katharine Jarmul is a Principal Data Scientist at Thoughtworks Germany focusing on privacy, ethics and security for data science workflows. Previously, she has held numerous roles at large companies and startups in the US and Germany, implementing data processing and machine learning systems with a focus on reliability, testability, privacy and security. She is a passionate and internationally recognized data scientist, programmer, and lecturer.

  • Supercharging Open Data with Open Privacy
Lars Grüter

Lars is currently working as a freelance and core developer for the image processing library scikit-image. With an education in electrical engineering and a focus in health and sensor technologies, he has been working as a research assistant on adaptive ultrasound imaging at the TU Dresden. As a student, he started contributing to the scientific Python ecosystem and discovered his interest for signal processing, Linux, and especially Python’s scientific ecosystem. He enjoys fine-tuning algorithms and discussing the finer points of designing an API.

  • Image processing with scikit-image
Maren Westermann

Dr Maren Westermann works as a machine learning engineer and holds a PhD in environmental science. She is a self taught Pythonista, an active open source contributor, especially to the library scikit-learn, and is a co-organiser of PyLadies Berlin where she hosts monthly open source hack nights.

  • How to increase diversity in open source communities
Maria Teleńczuk

Maria Teleńczuk, PhD, is a Data Scientist at Owkin and a PyLadies Paris Organiser.
At Owkin she works in a Federated Learning group where she investigates the strategies towards better analysis of and secure access to biomedical data.
Her experience varies from computational and experimental neuroscience to machine learning.
She taught Python at various courses and used it throughout her career.

  • Introduction to NumPy
Markus Gruber

Markus Gruber is a trained physicist and works as research scientist at Carl Zeiss. Together with his team he builds complex simulation and analysis tools in Python.

  • How to make the most precise measurement
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 ipycanvas, an interactive canvas library for Jupyter.

  • Interactive Data Science in the browser with JupyterLite and Emscripten Forge
Mike Müller
  • Getting started with JupyterLab
Milton Gomez

Born and raised in Nicaragua, I pursued a Mechanical Engineering undergraduate and master's degree in Taiwan. Having focused a section of my first master's on artificial intelligence, I moved onto the study of environmental fluid mechanics in France and applied deep learning techniques to predict weather events in Grenoble, an urbanized valley in the French Alps. I have now moved to Lausanne to form part of the dawn lab at UNIL, seeking to apply machine learning techniques in the tropical meteorology space.

  • Data-Driven Thresholding for Extreme Event Detection in Geosciences
Mojdeh Rastgoo

Currently working as a senior data scientist in Saint-Gobain. Python, machine learning and open source enthusiast.

  • Introduction to Python for scientific programming
Mridul Seth

I am currently working on the NetworkX open source project (work funded through a grant from Chan Zuckerberg Initiative!) Also collaborating with folks from the Scientific Python project (Berkeley Institute of Data Science), Anaconda Inc and GESIS, Germany. Before this I used to work on the GESIS notebooks and
I am also interested in the development and maintenance of the open source data & science software ecosystem. I try to help around with the Scientific Open Source ecosystem wherever possible. To share my love of Python and Network Science, I have presented workshops at multiple conferences like PyCon US, SciPy US, PyData London and many more!

  • Continuous and on demand benchmarking
  • Network Science with Python
Mx Chiin-Rui Tan
  • Education - Materials, methods, tools
Nicholas Hall

Senior R&D Engineer working at ABB Switzerland Ltd. I like to believe that there are always possibilities.

  • Discrete event simulations of 'all electric' mines
Noa Tamir

Noa has been active in OSS for some years now: she co-founded R-Ladies Berlin 2016, volunteered in PyData Berlin 2017, Founded satRday Berlin in 2018, WiMLDS Berlin in 2019, volunteered in useR! Toulouse 2019, was a speaker at PyConDE & PyData Berlin 2019, co-maintains the useR! knowledgebase and co-chaired PyConDE & PyData Berlin 2022.

Along side this she went from being a data scientist to a director of data science at respectable companies, and later became a freelance consultant. Since March 2022 she is employed at Quansight as a Contributor Experience Lead working with Matplotlib and Pandas. Noa has a Bsc in Physics, a Msc in Economics and Business Science and a MRes in Economics.

  • [Maintainers Track] Contributor Experience & Diversity
  • What is Contributor Experience?
Olivier Grisel

Olivier Grisel is a software engineer at Inria and a maintainer of the scikit-learn machine learning library.

  • Time Series Forecasting with scikit-learn's Quantile Gradient Boosted Regression Trees
Pamela Alejandra Bustamante Faúndez

Pamela Bustamante is a PhD candidate in Engineering Sciences from Pontificia Universidad Católica de Chile. Previously she did a Master's Degree in Industrial Engineering, and studied Industrial Civil Engineering.
She has been using Python since the start of her doctoral studies. Because of her love for the Python language, she participates as a co-organizer (and co-founder) of the groups "Python Chile" and "PyLadies Santiago de Chile" in Chile.
Currently, she is doing an internship in the context of her PhD in Lille, France. This talk is part of her Ph.D. Thesis in Engineering Sciences at the Pontificia Universidad Católica de Chile.

  • Discovering Mathematical Optimization with Python
Pierre-Olivier Simonard

Data Engineer at Quansight and teacher at the University of Strasbourg, I'm a python enthusiast since 2008. My main centers of interest are open source software, data visualization, Python, SQL, and 3D Printing.

  • Pragmatic Panel: Build and Deploy Complex Data-Driven WebApps
Reimar Bauer

I work at the Forschungszentrum Jülich GmbH as RSE. In 2010 I started the PythonCamp together with Peter Hecker and Christian Scholz. I have been maintaing the OSD Mission Support System for several years. Since 2013 I am a fellow of the Python Software Foundation. More:

  • Open Source Mission Support System for research aircraft missions
Roman Yurchak

Roman Yurchak has a background in computational physics, and is currently working as a consultant for data science and WebAssembly related projects at Symerio. He is also a core developer at the Pyodide and (previously) scikit-learn projects.

  • [Maintainers track] Python in the browser
  • Scientific Python in the browser with Pyodide
Serge « sans » Paille

Sometimes a compiler engineer, sometimes a woodworker, sometime a wizard of the coast. Developper of the Pythran compiler as a hobby.

  • Discover Pythran through 10 code samples
Thorsten Beier
  • [Maintainers track] Python in the browser
  • Interactive Data Science in the browser with JupyterLite and Emscripten Forge
Tim Hoffmann

Tim Hoffmann is a physicist and software expert passionate to bring science and high-quality software together. He works as Simulation Architect Digital Twin at Carl Zeiss, where he covers all aspects from coding, architecture, training up to software strategy. Tim is an active contributor in the Python open source community. In particular, he is core developer and API lead for the visualization library matplotlib.

  • Lessions learned from 10 years of Python in industrial reseach and development
  • Effectively using matplotib
Vaibhav Srivastav

I am a Data Scientist and a Masters Candidate - Computational Linguistics at Universität Stuttgart. I am currently researching on Speech, Language and Vision methods for extracting value out of unstructured data.

In my previous stint with Deloitte Consulting LLP, I worked with Fortune Technology 10 clients to help them make data-driven (profitable) decisions. In my surplus time, I served as a Subject Matter Expert on Google Cloud Platform to help build scalable, resilient and fault-tolerant cloud workflows.

Before this, I have worked with startups across India to build Social Media Analytics Dashboards, Chat-bots, Recommendation Engines, and Forecasting Models.

My core interests lie in Natural Language Processing, Machine Learning/ Statistics and Cloud based Product development.

Apart from work and studies, I love travelling and delivering Workshops/ Talks at conferences and events across APAC and EU, DevConf.CZ, Berlin Buzzwords, DeveloperDays Poland, PyCon APAC (Philippines), Korea, Malaysia, Singapore, India, WWCode Asia Connect, Google DevFest, and Google Cloud Summit.

  • Introduction to Audio & Speech Recognition
Valerio Maggio

Valerio Maggio is a Data scientist, fellow at the Software Sustainability Institute, and a casual "Magic: The Gathering" wizard. He holds a Ph.D. in Computer Science with a thesis on Machine Learning for Software Maintainability, and was previously appointed Senior Research Associate at the University of Bristol. Valerio is well versed into open source software, and best software development practice, specifically focusing on scalable and reproducible machine learning pipelines. Valerio is an active member of the Python community: over the years he has led the organisation of many international conferences like PyCon/PyData Italy/EuroPython, and EuroSciPy.

  • Introduction to PyTorch
Vincent Maladiere

Research Engineer at INRIA and AP-HP, I contribute to scikit-learn and focus on survival analysis.

I have a keen interest in machine learning, start-ups and biotech.

I'm a first-time speaker to EuroScipy, eager to meet the community :)

  • Introduction to SciPy
Wolf Vollprecht

Wolf studied robotics at ETH Zurich and Stanford University. After completion, he worked on many impactful Open Source projects: xtensor, xsimd, jupyter, jupyterlab and more. Most recently he initiated the mamba package manager alongside the boa and quetz projects and supports conda-forge as a core developer.

Wolf also started the RoboStack project to streamline the installation of robotic software on Windows, OS X and Linux, and pushed the intersection of data science and robotics by bringing Robotics to Project Jupyter.

  • conda-forge, mamba, boa and quetz - the evolution of package management for data science and beyond
  • conda-forge: supporting the growth of the volunteer-driven, community-based packaging project