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.

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.

LInkedin: https://linkedin.com/in/axsaucedo
Twitter: https://twitter.com/axsaucedo
Github: https://github.com/axsaucedo
Website: https://ethical.institute/

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.

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

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.

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.

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.

• PhD in Mathematics
• worked as Analyst and Data Scientist
• Mathematical Modelling and Optimization Expert @Palaimon GmbH (current)

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.

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.

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.

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).

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.

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.

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.

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.

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).

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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

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 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 US, SciPy US, PyData London and many more!

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

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.

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

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.

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.

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: http://www.blog.pythonlibrary.org/2018/11/26/pydev-of-the-week-reimar-bauer/

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.

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

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.

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.

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.

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 :)

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.