Abel S. Siqueira
  • Where is the flock? The use of graph neural networks for bird identification with meteorological radar.
Adrin Jalali

Adrin works on a few projects, including skops which tackles some of the MLOps challenges related to scikit-learn models. He has a PhD in Bioinformatics, has worked as a consultant, as well as working in an algorithmic privacy and fairness team. He's also a core developer of scikit-learn and fairlearn.

  • Let’s exploit pickle, and `skops` to the rescue!
Aleksandra Płońska

Lawyer, a graphic designer with a passion for promoting data science tools. Open source enthusiast. From 2019, Executive Director at MLJAR - (the best open-source AutoML available).

  • From Complex Scientific Notebook to User-Friendly Web Application
Alexander Fabisch

Alexander Fabisch received his diploma degree in computer science from the University of Bremen in 2012. From 2012 to 2017 he worked as a researcher at the robotics research group of the University of Bremen and since 2017 he works at the Robotics Innovation Center of the German Research Center for Artificial Intelligence (DFKI). He obtained his doctoral degree from University of Bremen in 2020. His scientific interests are in the fields of machine learning and black-box optimization with robotic applications and a focus on learning manipulation behaviors.

  • Transformations in Three Dimensions
Allan Folting

Allan is a product manager at Databricks mainly working on PySpark.
He is passionate about helping people make sense of data and has focused on that his whole career.

  • Scaling pandas to any size with PySpark
Andrea Guzzo

AI Tech Leader at MDPI, Founder and organiser of PythonBiellaGroup, Computer scientist and Nerd by Night.

  • GPT generated text detection: problems and solution in the scientific publishing
Arkadiusz Trawiński, PhD

Product Lead of Data Scientist team in IT monitoring department of ING. PhD in Physics, BSc in Computer Science.

  • Incidents management using Hawkes processes and other Tech AIOps projects in ING
Artem Kislovskiy

As a software engineer with a degree in computational physics, Artem brings a unique perspective to the intersection of science and technology. With a passion for both computations and physics, Artem has applied his knowledge and skills to various projects, including computational fluid dynamics and fluid-structure interactions. While Artem's background is in physics, he has found a love for software development and is now a full-time software engineer. However, his passion for physics and desire to make a meaningful impact in scientific research has led him to explore how software engineering principles can best be applied in scientific projects.

  • Why I Follow CI/CD Principles When Writing Code: Building Robust and Reproducible Applications
Arturo Amor

I did my PhD in theoretical quantum physics at the National Autonomous University of Mex-
ico (UNAM). I currently work at the INRIA foundation as part of the scikit-learn consortium, mostly in charge of maintaining the scikit-learn documentation.

  • Content-based recommendation-system for the examples in sphinx-gallery
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, Cheuk is now the Developer Advocate at Anaconda. Cheuk also contributes to multiple Open Source libraries like Hypothesis and Pandas.

Besides her work, Cheuk enjoys talking about Python on personal streaming platforms 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), 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.

  • Contributor, Developer and Volunteer Experience: Navigating Challenges Beyond Code
  • Generating Data Frames for your test - using Pandas stratgies in Hypothesis
Dr. Milos Cuculovic

PhD in Computer Science, IT executive, certified project and product manager oriented to complex assignments with 12 years` working experience in the academic publishing business, focusing on distinct R&D, technology innovation, system administration and information security projects covering ML/AI, Web development and Linux infrastructure.

  • GPT generated text detection: problems and solution in the scientific publishing
Duarte Carmo

I'm a technologist, born and raised in sunny Portugal, now based in Copenhagen. My work lies in the intersection of Machine Learning, Data, Software Engineering, and People. I'm in love with Technology, and how it can improve people's lives.

In the past, I've worked in Consumer Electronics, Public Institutions, Big Three Management Consulting, and Startups. The common thread? Solving problems end-to-end.

Now, I run my own ML consulting shop, where I focus on solving tough problems end-to-end.

  • Exploring Geospatial data for Machine Learning using Google Earth Engine: An introduction
Ezi Ozoani

Research engineer excited and working on applied AI research and quantum ML and the intersections of ethical and inclusive practises.

  • Model Documentation: The Keystone towards Inclusivity and Accessibility
Fabian Hoppe

I recently obtained a PhD in numerical mathematics from the university of Bonn. Currently, I am postdoctoral researcher in the Scientific Machine Learning group at the Institute for Software Technology of the German Aerospace Center (DLR).

  • The Helmholtz Analytics Toolkit (Heat) and its role in the landscape of massively-parallel scientific Python
Franck Charras

I graduated as a machine learning research engineer in 2016, with a specialization in NLP. I co-founded Sancare a start-up company that aims at bringing NLP-based solutions for medical data analysis to hospitals, and that has made a place for itself in the market with a performant NLP-powered billing assistant for medical stays. I'm now working at INRIA, France as a Machine Learning Research Engineers, focused on performance computing.

  • Exploring GPU-powered backends for scikit-learn
  • Interoperability in the Scientific Python Ecosystem
Geir Arne Hjelle

Geir Arne teaches Python at Real Python. He has a background in mathematics and has worked with data analysis in different fields, such as electricity markets, satellite geodesy, and computer vision. In his spare time, Geir Arne enjoys hammock camping, square roots, and aimless forest wandering.

  • Introduction to NumPy
Giada Pistilli

Giada Pistilli is a philosophy researcher specializing in ethics applied to Conversational AI. Her research is mainly focused on ethical frameworks, value theory, and applied and descriptive ethics. After obtaining a master’s degree in ethics and political philosophy at Sorbonne University, she pursued her doctoral research in the same faculty. Giada is also Principal Ethicist at Hugging Face, where she conducts philosophical and interdisciplinary research on AI Ethics and content moderation. Her publications, resume, and contact information are available on her website.

  • Integrating Ethics in ML: From Philosophical Foundations to Practical Implementations
  • Contributor, Developer and Volunteer Experience: Navigating Challenges Beyond Code
Gil Forsyth
  • Ibis: A fast, flexible, and portable tool for data analytics.
  • Ibis: Because SQL is everywhere but you don't want to use it
Guillaume Lemaitre
  • Image processing with scikit-image
  • Get the best from your scikit-learn classifier: trusted probabilties and optimal binary decision
Hyukjin Kwon

Hyukjin is a Databricks software engineer as the tech-lead in OSS PySpark team, Apache Spark PMC member and committer, working on many different areas in Apache Spark such as PySpark, Spark SQL, SparkR, infrastructure, etc. He is the top contributor in Apache Spark, and leads efforts such as Project Zen, Pandas API on Spark, and Python Spark Connect.

  • Scaling pandas to any size with PySpark
Jacob Tomlinson

Jacob Tomlinson is a senior software engineer at NVIDIA. His work involves maintaining open source projects including RAPIDS and Dask. He also tinkers with Opsdroid in his spare time. He lives in Exeter, UK.

  • Deploying multi-GPU workloads on Kubernetes in Python
Janos Gabler

Author of estimagic | PhD in economics | Expert in numerical optimization | Building Bandsaws, Pizza Ovens and Furniture

  • Estimagic: A library that enables scientists and engineers to solve challenging numerical optimization problems
  • Introduction to numerical optimization
Joan Massich
  • Image processing with scikit-image
Jonathan Striebel

Jonathan is a ML software engineer at Aignostics in Berlin, Germany. He works on machine-learning pipelines for medical image analysis, ensuring scalability and maintainability. Also, he’s an active member of the Zarr community, and one of the authors of the Zarr v3 specification.

  • From Implementation to Ecosystem: The Journey of Zarr
Joost Göbbels

Thesis intern at the AI4Fintech research lab at ING. Joint MSc student Mathematics & Computer Science. BSc in Mathematics

  • Incidents management using Hawkes processes and other Tech AIOps projects in ING
Joris Van den Bossche

I am a core contributor to Pandas and Apache Arrow, and maintainer of GeoPandas. I did a PhD at Ghent University and VITO in air quality research and worked at the Paris-Saclay Center for Data Science. Currently, I work at Voltron Data, contributing to Apache Arrow, and am a freelance teacher of python (pandas).

  • Pandas 2.0 and beyond
  • Interoperability in the Scientific Python Ecosystem
Julien Jerphanion

Julien is a Scientific Software Engineer at QuantStack. He holds a MSc. Computer Science & Engineering from Université de Technologie de Compiègne and a MSc. Applied Mathematics, Computer Vision and Machine Learning from École Normale Supérieure Paris-Saclay.

Julien is involved in the Scientific Python ecosystem and co-maintain scikit-learn

Prior to joining QuantStack, Julien worked as a Research Software Engineer at Inria.

  • Sparse Data in the Scientific Python Ecosystem: Current Needs, Recent Work, and Future Improvements
Kacper Leśniara

Co-creator of the SRAI library,
An ML Engineer passionate about the geospatial domain and an author of highway2vec.
Background in Computer and Data Science from the Wrocław University of Science and Technology and a proud member of the KRAINA Lab tackling geospatial problems. MLOps Engineer @ GetInData

  • Introduction to Geospatial Machine Learning with SRAI
Kai Striega

Kai is a SciPy maintainer and a software developer at BHP. He is interested in all things Python, particularly in pushing Python's performance to the language's limits.

  • Timing and Benchmarking Scientific Python
Kamil Raczycki

Co-creator of SRAI library.
Spatial Data Scientist working at Allegro during the day and passionate open-source developer and geospatial researcher at night.
Graduated Master of Science in Data Science @ Wrocław University of Science and Technology.

  • Introduction to Geospatial Machine Learning with SRAI
Loïc Estève

Loïc 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.

  • My foray from Scientific Python into the Pyodide / WebAssembly universe
Maarten Breddels

Maarten Breddels is an entrepreneur and ex-scientist mainly working with Python, C++, and Javascript in the Jupyter ecosystem. He is the creator of Solara, ipyvolume, and Vaex and Co-founder of Widgetti. His expertise includes fast numerical computation, API design, 3D visualization, and building data apps. He has a Bachelor's in ICT, a Master's, and Ph.D. in Astronomy, and he likes to solve real problems.

  • Solara: A Pure Python, React-style Framework for Scaling Your Data Apps
Marc Garcia

Marc is a pandas core developer and the release manager for pandas 1.5 and 2.0. He is also an Ibis and ASV core developer, a fellow of the Python Software Foundation, and the VP of infrastructure at NumFOCUS. Marc works as an independent software and data consultant for clients such as Bank of America, Unilever, Bumble, Tesco and NTT Communications.

  • Developing pandas extensions in Rust
Marco Gorelli

Marco works as a Senior Software Engineer at Quansight Labs. He mainly works on pandas and the DataFrame Consortium (as part of work) and on polars (as a volunteer).

  • DataFrame-agnostic code: are we there yet?
Maren Westermann

Dr Maren Westermann works as a machine learning engineer at DB Systel GmbH 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.

  • Contributor, Developer and Volunteer Experience: Navigating Challenges Beyond Code
  • Building divserve open source communities - learnings from PyLadies Berlin’s monthly open source hack nights
Michele "Ubik" De Simoni

"Ever Tried. Ever Failed. Try Again. Fail Again. Fail Better. (Beckett)"

I work full-time as a Senior Machine Learning Scientist (handling many Data Engineering tasks as well) with a focus on ML for medical imaging at Align Tech.

Current tech hobbies: working with LLMs, worrying about AI risks (focusing on x-risks and Alignment, but it's not looking too good even for more "mundane" threats), and contributing to AI Safety.

I was active as a Python & Data Science/Machine Learning teacher and speaker for local and European meetups and conferences, but that ground to a halt due to the plague. I plan to resume in 2023, as I love traveling and teaching!

I can usually be found next to some source of caffeine, be it a chawan of Matcha or a cup of V60, bookstores & libraries, cooking classes, tabletop RPGs, and Python/ML/Data meetups.

  • (in)Complete introduction to AI Safety
Mike Müller

I am a Python user since 1999 and been teaching Python since 2004, including 60+ conference tutorials.

  • Getting started with JupyterLab
Milton Gomez

PhD student from Nicaragua studying the application of machine learning to environmental sciences (more specifically tropical meteorology) in Lausanne.

  • Introduction to Python for scientific programming
  • Chalk’it: an open-source framework for rapid web applications
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. Before this I used to work on the GESIS notebooks and gesis.mybinder.org.
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, (Euro)SciPy, PyData London and many more!

  • Network Analysis Made Simple (and fast!)
  • Interoperability in the Scientific Python Ecosystem
Nicolas Rougier
  • The Graphic Server Protocol, a joint effort to facilitate the interoperability of Python scientific visualization libraries
Nikita Churikov

For 7 years I worked primarily with python and applied it to a variety of tasks: Machine Learning in NLP, Drug discovery and Computer vision. Developed REST APIs for these models, web applications using Flask and Django and cli apps with python std library or click library.

I’m also interested in Julia and rust languages in general and in C++ for computer vision.

My full CV as a developer is available on LinkedIn.

  • Build Drug Discovery web applications with PyScript, Ketcher and rdkit
Olga Lyashevska

Currently I work as Research Software Engineer at the Netherlands eScience Center in Amsterdam. Pior to that I worked as a Research Fellow at the Atlantic Technological University in Galway, Ireland. I have a passion for scientific programming, open source software and linux. I am also a lecturer and a PhD supervisor.

  • Where is the flock? The use of graph neural networks for bird identification with meteorological radar.
Olivier Grisel

Machine Learning software engineer at Inria and member of the maintainers' team of the scikit-learn open source project.

  • Exploring GPU-powered backends for scikit-learn
  • Interoperability in the Scientific Python Ecosystem
  • Predictive survival analysis with scikit-learn, scikit-survival and lifelines
Phillip Cloud

I'm fascinated by a variety of problems related to computers. I've solved hard problems in a variety of software engineering domains including digital video, Rust, systems programming, computer vision, and analytics. I'm currently helping build next generation Python analytics tooling at Voltron Data.

  • Ibis: A fast, flexible, and portable tool for data analytics.
  • Ibis: Because SQL is everywhere but you don't want to use it
Piotr Gramacki

Co-creator of SRAI library. Master of Science in Data Science @ Wrocław University of Science and Technology. Machine Learning Engineer @ Brand24

  • Introduction to Geospatial Machine Learning with SRAI
Piotr Płoński

Software engineer trying to make data science tools easier to use for everyone. Working on open source tools: mljar-supervised and mercury.

  • From Complex Scientific Notebook to User-Friendly Web Application
Piotr Szymański

Piotr Szymański is a scientist with a mathematical and computer science background. He obtained his Ph.D. in Computer Science at Wrocław University of Science and Technology in 2020. As a scholar, he visited Stanford University, Hasso Plattner Institute in Potsdam, Technical University of Sydney, Dortmund Technical University, and Josef Stefan Institute in Ljubljana. He is the primary author of the scikit-multilearn library for multi-label classification. He also has extensive corporate R&D experience. He was one of the authors of the ML/AI layers of Avaya Conversational Intelligence, a contact-center personnel support solution used widely in American call centers. Currently, he leads a Spatial AI group at the Department of Artificial Intelligence at Wrocław University of Science and Technology, Poland.

  • Introduction to Geospatial Machine Learning with SRAI
Richard Shadrach

I am a core contributor to pandas. I earned a PhD in Mathematics from Michigan State University studying Arithmetic Geometry and am now a Director of Data Science at 84.51° specializing in large scale optimization problems.

  • Pandas 2.0 and beyond
Ritchie Vink

Ritchie Vink is the author of the Polars DataFrame library and query engine.
He has been working as a software engineer and machine learning engineer for 8 years.
Before he started polars, he did many side projects on varying topics in computer science and statistics.

  • Keynote on polars
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 & Thebe: Community-driven tools for awesome open science communication with Jupyter[lite] backed computation
Sebastian Berg

Sebastian Berg is a NumPy maintainer and steering council member working at NVIDIA. He started contributing to NumPy during his undergrad and PhD and Physics and continued working on NumPy at the Berkeley Institute for Data Science before continuing to contribute at NVIDIA.

  • What-not to expect from NumPy 2.0
  • Interoperability in the Scientific Python Ecosystem
Stefania Delprete

Stefania studied physics and worked in IT and data science in the UK, Germany and Italy. She's involved with Python, Mozilla and data science communities, and data science projects.

She manages the Italian chapter of effective altruism and a professional group of experienced or aspiring people in the field of data science, machine learning and artificial intelligence involved in that community of effective altruists. She recently joined ENAIS (European Network for AI Safety) as executive director.

  • Contributor, Developer and Volunteer Experience: Navigating Challenges Beyond Code
Stefanie Molin

Stefanie Molin is a software engineer and data scientist at Bloomberg in New York City, where she tackles tough problems in information security, particularly those revolving around data wrangling/visualization, building tools for gathering data, and knowledge sharing. She is also the author of Hands-On Data Analysis with Pandas, which is currently in its second edition. She holds a bachelor’s of science degree in operations research from Columbia University's Fu Foundation School of Engineering and Applied Science, as well as a master’s degree in computer science, with a specialization in machine learning, from Georgia Tech. In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken among both people and computers.

  • Introduction to Data Analysis Using Pandas
Stefanie Sabine Senger

Historian (PhD) that went astray. I'm teaching Data Science to career changers at Le Wagon and started contributing to scikit-learn during the last months.

  • Introduction to scikit-learn
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.

  • MyST & Thebe: Community-driven tools for awesome open science communication with Jupyter[lite] backed computation
Szymon Woźniak

Co-creator of SRAI library,
Passionate AI Researcher and ML Engineer working in NLP and GeoAI.
Graduated from the Wrocław University of Science and Technology with a Bachelor's in Computer Science and a Master's Degree in Data Science

  • Introduction to Geospatial Machine Learning with SRAI
Tim Head

I contribute to scikit-learn. In the past I helped build mybinder.org and scikit-optimize. Way back in the history of time I was a particle physicist at CERN and Fermilab.

  • Interoperability in the Scientific Python Ecosystem
Tim Hoffmann

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

  • Accelerating your Python code - a systematic overview
  • Introduction to matplotlib for visualization in Python
Tim Mensinger

I'm a Ph.D. candidate in economics at the University of Bonn, currently working on topics related to computational econometrics. My projects range from contributing to optimization libraries to implementing statistical methods or models of human behavior. I try to develop software that is easy to use and extend. Besides that, I'm a big advocate for reproducibility and the open-source philosophy, which I try to support by being an active member of the Open Source Economics initiative.

  • Introduction to numerical optimization
Tobias Raabe
  • Introduction to numerical optimization
Vadim Nelidov

Vadim Nelidov is a Lead Data Science consultant at Xebia Data with diverse data & research experience in a variety of industries from energy sector to skincare and agriculture. He also has a research background in decision making sciences as well as several publications in this domain. Throughout his years in the data world, Vadim has been combining advanced data science with practical insights to make data work with an impact for the world. He aspires to see far beyond what is on the surface and get to the essence of the problems.

Vadim is passionate about sharing his knowledge and insights, believing that Data literacy should not be a privilege of a few. And his goal is to be there to make this a reality. Making the intricacies of data science intelligible and uncovering the regularities hiding in the data is a major source of inspiration for Vadim. With this goal in mind, he combines his years of experience in consulting with his background in statistics, research and teaching to make this knowledge accessible to businesses and individuals in need.

  • Anomaly Detection in Time Series: Techniques, Tools and Tricks
Valerio Maggio

Valerio Maggio is a Researcher, and a Data scientist Advocate at Anaconda. He is well versed in open science and research software, supporting the adoption of best software development practice (e.g. Code Review) in Data Science. He has been recently awarded a fellowship from the Software Sustainability Institute (profile) focused on developing open teaching modules [1][2] on Privacy-Preserving Machine learning technologies. Valerio is also an open-source contributor, and an active member of the Python community. Over the last twelve years he has contributed and volunteered in the organization of many international conferences and community meetups like PyCon Italy, PyData, EuroPython, and EuroSciPy. All his talks, workshop materials and open source contributions are publicly available on his Speaker Deck and GitHub profiles.

  • PPML: Machine Learning on data you cannot see
Vincent Maladiere

Machine Learning Engineer at Inria • Contributor of scikit-learn, skrub and hazardous • Eager to talk about deploying stuff and MLOps :)

  • Predictive survival analysis with scikit-learn, scikit-survival and lifelines
Wolf Vollprecht

Wolf is the CEO of prefix.dev, a company that specializes in cross-platform package management with the open source mamba package manager and more.
He is a core member of the conda-forge project, the RoboStack project and main author of the mamba package manager.

  • Python versioning in a changing world