EuroSciPy 2025 — the speakers, verified

Krakow, Poland · August 2025 · organized by EuroSciPy

53 speakers below were extracted from the event's public agenda, and EuroSciPy 2025 publishes its own site.

Who spoke, and about what

• Jon Nordby — Jon is a Machine Learning Engineer specialized in IoT systems.
  • Sensor data processing on microcontrollers with MicroPython source
• Olivier Grisel — Olivier is an Open Source Fellow at probabl and a core contributor to the scikit-learn machine learning library.
  • Predictive modeling for imbalanced classification using scikit-learn source
• Guillaume Lemaitre — I have a PhD in computer science and have been a scikit-learn and imbalanced-learn core developer since 2017. I am curre
  • Predictive modeling for imbalanced classification using scikit-learn source
  • Skrub: machine learning for dataframes source
• Jérôme Dockès
  • Skrub: machine learning for dataframes source
• Riccardo Cappuzzo
  • Skrub: machine learning for dataframes source
• Cheuk Ting Ho — After having a career in Data Scientist and Developer Relations, Cheuk dedicated her work to the ope
  • Deploy your Machine Learning model with Fast API source
• Anuradha Kar
  • Automated Chess Analysis: Real-Time Move Detection and Game Narration Using Computer Vision and Large Language Models source
  • Guardians of Science: A Python Tutorial on a RAG-Powered Compliance Plug-In and Ethical AI tools source
• Likhita Yerra
  • Automated Chess Analysis: Real-Time Move Detection and Game Narration Using Computer Vision and Large Language Models source
  • Guardians of Science: A Python Tutorial on a RAG-Powered Compliance Plug-In and Ethical AI tools source
• Grzegorz Bokota
  • Use napari for easier interactive extraction of knowledge from images and other spatial data source
• Francesc Alted
  • Python-Blosc2: Compress Better, Compute Bigger! source
  • Compress, Compute, and Conquer: Python-Blosc2 for Efficient Data Analysis source
• Luke Shaw
  • Python-Blosc2: Compress Better, Compute Bigger! source
  • Compress, Compute, and Conquer: Python-Blosc2 for Efficient Data Analysis source
• Mike Müller — I've been teaching Python courses since 2004. According to my statistics, I've taught about 550 Pyth
  • Introduction to Python and JupyterLab source
• Umut Nefta Kanilmaz — I am a researcher and PhD candidate at the department of Geoinformatics at the University of Salzburg. My research focus
  • Introduction to NumPy and DataFrames source
• Justyna Szydłowska-Samsel
  • Introduction to Scikit-learn source
• Stefanie Molin — [Stefanie Molin](https://stefaniemolin.com) is a software engineer at Bloomberg in New York City, wh
  • Beyond the Basics: Data Visualization in Python source
• Anatoly Volkov
  • Using Cython and C++ kernels to speed up Python libraries source
• David Cortes
  • Using Cython and C++ kernels to speed up Python libraries source
• Jacob Tomlinson — Jacob Tomlinson is a senior software engineer at NVIDIA. His work involves maintaining open source p
  • GPU Python for the Real World: Practical GPU-Accelerated Python with RAPIDS source
• Jan Boelts
  • Pyro Meets SBI: Unlocking Hierarchical Bayesian Inference for Complex Simulators source
  • Beyond Likelihoods: Bayesian Parameter Inference for Black-Box Simulators with sbi source
• Maternus Herold
  • Beyond Likelihoods: Bayesian Parameter Inference for Black-Box Simulators with sbi source
• Frank Sauerburger
  • Annotating the dynamic: Type Annotation for DataFrames source
• Ole Bialas
  • Managing Scientific Data and Workflows with DataLad source
• Michał Szczepanik
  • Managing Scientific Data and Workflows with DataLad source
• Lucas Colley
  • Standardised Quantity/Unit APIs discussion source
  • A Hitchhiker's Guide to the Array API Standard Ecosystem source
• Juan Luis Cano Rodríguez — Juan Luis (he/him/él) is an Aerospace Engineer with a passion for tech communities, outreach, and su
  • Accelerate your scientific Python code with Rust source
• Jesse Grabowski
  • Recent Developments in Pytensor, the Successor Package to Theano source
• Ricardo Vieira
  • Recent Developments in Pytensor, the Successor Package to Theano source
• Janos Gabler
  • Let's rewrite optimagic from scratch in half an hour and see what we can learn source
• Francesco Bonazzi
  • Enhancing SymPy Algorithms with MatchPy's Efficient Pattern Matching source
• Jakub Adamczyk
  • Machine learning for ecotoxicology and bee pesticide toxicity prediction source
• Samarth Bachkheti
  • Python for subsea engineering: A case study on seabed object detection using AI/ML source
• Manuel Jürgensen
  • Python Framework for Large-Scale Radar Data Generation and Visualization source
• Loïc Estève
  • PyPI in the face: running jokes that PyPI download stats can play on you source
• Tim Head
  • Array API and library dispatching source
• Sebastian Berg
  • Understanding Dispatching Approaches in the Scientific Python Ecosystem source
  • Array API and library dispatching source
• Kai Striega
  • Maintaining People, Not Just Projects: Attracting and Retaining Talent in FOSS source
• Dawn Wages
  • The Fellowship of the Stack: Scientific Discovery in Python source
• Mridul Seth
  • Units next to your Data: Arrays with Scipp source
• Oliver Zeigemann
  • Routing Strategies for Heterogeneous GenAI Systems: Lessons from Real-World Practice source
• Ada Böhm
  • Breaking the Constraints of Linear Notebook Environments source
• Aditi Juneja
  • Understanding Dispatching Approaches in the Scientific Python Ecosystem source
• Michał Wroński
  • Numba-MPI & PyMPDATA: JIT-compilation and multi-threading for high performance computing in Python source
• Florian Wilhelm
  • Solving Hard Optimization Problems with Pyomo and HiGHS: A Practical Introduction source
• Piotr Ludynia
  • Efficient and accurate models for peptide function prediction source
• Franciszek Job
  • Efficient processing pipelines for large scale molecular datasets in Python source
• Davide De Marchi
  • Voilà Meta-Dashboards for Streamlined Geospatial Data Visualization source
• Pedro Garcia Lopez
  • Processing Cloud-optimized data in Python (Dataplug) source
• Daniel Alejandro Coll Tejeda
  • Processing Cloud-optimized data in Python (Dataplug) source
• Agnieszka Żaba
  • Can Your Research Notebook Survive a Code Update? On maintaining Reproducibility with Continuous Integration source
• Jakob Zahn
  • ELVA - Local-First Real-Time Collaboration Apps in Your Terminal source
• Tiziano Zito
  • ELVA - Local-First Real-Time Collaboration Apps in Your Terminal source
• Adam Staniszewski
  • How To Accelerate Molecular Insights - Efficient Distance Calculations In Python source
• Igor Tatarnikov
  • The BrainGlobe initiative - image analysis in a common coordinate space. source

Questions about EuroSciPy 2025

Who spoke at EuroSciPy 2025?

53 speakers we hold a record for, listed below with the session each one gave. The list comes from the conference's own published agenda, so it is who actually appeared rather than who applied or who paid.

When and where was EuroSciPy 2025?

August 2025, in Krakow, run by EuroSciPy. The agenda it was taken from is linked at the top of this page.

Are the talk titles real?

61 of the 61 records carry the session title exactly as the agenda printed it, so every one below is quoted.

Can I contact these speakers?

Not through us. We hold no contact details and no fees. Each entry links to the agenda page it came from, and that is the route.