PyData Eindhoven 2025

Achraff Adjileye is a research engineer passionate about football analytics and artificial intelligence. He is the founder of the BALLER project, which aims to build a foundational model for football analytics—powering the next generation of context-aware football analysis, much like GPT revolutionized text understanding.

His vision: Football is the ultimate team sport, yet most analytics treat players as isolated individuals. Players are often represented by radar charts of individual statistics, ignoring the rich collective context that shapes their identity. While this approach transformed data-driven scouting, it is inherently prone to misinterpretation, leading to costly mistakes in transfers and strategic decisions. Achraff works every day to create a football analytics world that respects the collective DNA of the beautiful game.

Albert Podusenko is CEO of Lazy Dynamics, building RxInfer — a Bayesian inference engine for real-time, uncertainty-aware AI. He holds a PhD from TU Eindhoven in probabilistic machine learning.

PhD student at the University of Groningen investigating the one-on-one dribbles.

Ali Kohan:
Data Scientist and AI consultant with a background in computer vision and deep learning. After several years working as a computer vision engineer, I am now focused on building recommendation and personalization systems. Passionate about applied AI, I enjoy exploring how intelligent systems can better understand and adapt to human behavior.

Reza Ebrahimpour:
Software engineer with a decade of experience building scalable, cloud-native systems in the JVM ecosystem. Passionate about microservice architectures, data-driven design, and high-availability services. Recently focused on integrating machine learning and AI solutions into production systems at Bol.

With a background in mathematics and econometrics, Annemarijn combines analytical skills with practical solutions. As a data scientist, she is passionate about solving complex puzzles with mathematics and applying her knowledge to real-world problems. At Pipple, she uses her skills to develop practical, effective and creative solutions in various sectors.

TBD

I have a strong mathematical background and more than 10 years of experience working with data. Over the years, my focus has been on various applications of ML models, research to support decision-making, and personalizing customer experiences for projects with millions of users.

Currently, I'm Sr. Data & AI Specialist at Maxeda DIY Group, where I focus on advancing scalable AI solutions and integrating machine learning into business operations.

Florents (Flo) Tselai is a data generalist, open-source developer, and PostgreSQL contributor. He has authored multiple database extensions, primarily for PostgreSQL, and also for SQLite and DuckDB.

His work sits at the intersection of database engineering, AI, web crawling, and data journalism - blending research, engineering, and leadership along the way.

He is also the creator of diofanti.org, a civic-tech platform that promotes government transparency and citizen empowerment, enabling people to track public spending and decisions in Greece. https://github.com/Florents-Tselai

Fotball Data Scientist/AI Engineer @SportAnalytics
Data Science and AI's Master Student @UNITS
Former Data Science Intern @RBFA

Geert Jongen is a System Architect for Data & Analytics at Vanderlande, where he designs and evolves the company’s data platform toward a federated data mesh. Before that, he worked as a data consultant at Pipple for five years. With a background in data engineering, analytics, and data science, he focuses on building scalable data architectures that empower teams through autonomy and governance.

I graduated in statistics in 2018 and have been working in data analytics ever since, across a variety of roles. I am currently the Head of Sport Sciences at GRAET, a company building a platform to help aspiring ice hockey players develop their potential. Alongside this, I work as a part-time data analyst for one of the major Czech ice hockey clubs. My work combines a passion for sports with a love of data. Outside of work, I enjoy playing the drums, riding my bike, and debating whether pineapple belongs on pizza — though as a fan of pizza Hawaii, I’m firmly in the “yes” camp.

Max Brouwer (MSc) is a Data Scientist at the Royal Dutch Lawn Tennis Association (KNLTB). He graduated cum laude from the University of Groningen in 2021, earning a Master’s degree in Sport Science with a focus on applying computer vision and machine learning techniques to tennis.

At the KNLTB, Max contributes to both the Sport Science Team and the Data Team. In the Sport Science Team, he works on projects involving sensor technology, load monitoring, and match analysis. In the Data Team, his expertise extends to recreational tennis and padel, including the development of the new padel rating system.

Sports nerd with over 30 years of experience as a fan, 10 years of experience working in data, and 5 years combining both to support professional teams (across football, baseball and ice hockey) in better understanding their sports.

Rob de Wit-Liezenga is a freelance engineer who has worked in different data-related roles throughout his career. He's been a data analyst, data platform engineer, developer advocate, and customer success engineer. He enjoys work where he can combine hard tech with a people-focused role.

He has spoken at and co-organized various conferences in the past, including PyData Eindhoven. He enjoys meeting fellow pythonistas, learning from them, and sharing some of his own learnings.

Nowadays, Rob works as a CSE for Anyscale, where he helps customers deploy and optimize their infrastructure for large-scale AI workloads. Outside work, he enjoys photography, learning Spanish, hiking, and climbing.

Tom Koopen is a highly experienced professional in computer vision and deep learning. He holds a Master’s Degree in Applied Physics from the University of Twente, specializing in optical measurement systems.

With over 25 years of experience in computer vision, Tom has worked with various companies in the Netherlands. Since 2013 he is an entrepeneur at “de tijdelijke expert”, assisting customers with the application of computer vision technology, focusing on measurements, identification, and sorting of products. Recently he founded “textilemining.eco” to build innovative machines for textile recycling.

He has designed lighting systems, selected and optimized cameras, and written software for thousands of hours. Some of his notable projects include inspecting plastic crates for contamination, improving the sorting of plastics, metals and flower bulbs. He developed a 3D scanner to recognize roof tiles for Luijtgaarden B.V. and measured colors during high-speed printing processes at QI Press Controls. Oh, and don’t forget the beer bottle inspection with 10 per second about 20 years ago.

24 year old Sport Science and Business Administration student at the University of Groningen, currently doing an internship as Data Scientist at the Royal Belgian Football Association (RBFA). Passionate about working with (soccer) data, and driven to excel in the fast-paced, performance-driven world of football.

Vi Chu is a data scientist at Vanderlande, where she develops scalable predictive maintenance solutions that help keep complex automated logistics systems running smoothly. She’s motivated by collaborative problem-solving and loves when a solution becomes simple, elegant, and easy for everyone to put into practice.

A results-driven data professional – focused on hype-free solutions tailored to business needs.

I am currently creating value at the National Institute of Geophysics and Volcanology (INGV), where I develop machine learning models in the Space Weather domain. My job is complemented by finding the hidden stories in data and make them accessible to stakeholders. I studied Physics in Italy (Napoli) and Germany (Frankfurt am Main), previously worked on Analytics in the strategic division of the world's largest professional services network, and in the Data Science department of the leading Italian publisher.

When not at work, I enjoy theatre, talking about finance or learning a new language.

I'm Yannick Mariman, a data engineer working at Pipple, working with IKEA to build an improved Retail Planning platform. Earlier in my career, I saw good data solutions failing because of a lack of proper workflows and orchestration. This led me to become more interested in tangible solutions that focus on robustness and stability.

Senior Python Developer and team lead with over 8 years of experience building large-scale data acquisition systems for international companies. Led teams in developing resilient scrapers, AI-powered sentiment analysis platforms, and predictive models for industries ranging from e-commerce to finance. Passionate about turning raw web data into actionable insights, sharing hands-on lessons from real-world projects at the intersection of Python, data engineering, and machine learning.