Summer School 2025 – Program & Speakers
Learn about this year’s Summer School program & speakers – more details and the full program will be announced soon!
Keynotes
Further information will be announced soon.
Jean-Philippe Vert is a Research Scientist & Professor in Machine Learning and Computational Biology. His long-term research goal is to understand how machines can learn from data and leverage this knowledge to drive scientific breakthroughs in biology and medicine.
He currently serves as the Chief R&D Officer at Owkin, a French-American AI biotech company focused on using artificial intelligence to find the right treatment for every patient. His work at Owkin is dedicated to advancing AI-driven drug discovery and development, with a particular emphasis on addressing unmet medical needs, starting with the fight against cancer.
Ludovic Denoyer is the Agent Research Team Lead at H Company.
Professor Shie Mannor is a faculty member in the Department of Electrical Engineering at the Technion, where he is affiliated with the Technion Machine Learning Center and the Grand Technion Energy Program. He also serves as a visiting professor at Cornell Tech in New York City. His research focuses on machine learning, the control of large and stochastic systems, and game theory.
Charles-Albert Lehalle is currently a Professor at Ecole polytechnique in Paris teaching and researching on liquidity, price formation, and the use of AI on financial markets. Previously, he has been Global Head, Quantitative Research & Development, at the Abu Dhabi Investment Authority (ADIA) during three years. He started his career being in charge of embedded AI solutions at the Renault Research Center and moved to the financial industry with the emergence of automated trading in 2005. He was Global Head of Quantitative Research at Crédit Agricole Cheuvreux, and Head of Quantitative Research on Market Microstructure at Crédit Agricole Corporate Investment Bank, before joining to Capital Fund Management (CFM) for 7 years.
On the academic side, Pr. Lehalle received the 2016 Best Paper Award in Finance from Europlace Institute for Finance (EIF) and has published more than eighty academic papers and book chapters. He co-authored the books “Market Microstructure in Practice” (World Scientific Publisher, 2nd edition 2018), analyzing the main features of modern markets; and “Financial Markets in Practice” (World Scientific Publisher 2022), explaining how the connected network of intermediaries that makes the financial system is shaping prices formation; he co-edited with Pr Agostino Capponi the book “Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices” (Cambridge University Press, 2023).
Pr. Lehalle is also a member of the Scientific Directory of the Louis Bachelier Institute, Lecturer at UC Berkeley and Paris 6 Sorbonne Université and Ecole Polytechnique “Probability and Finance” Master.
Tutorials
Further information will be announced soon.
Aymeric Dieuleveut is a Professor in Statistics in the applied mathematics department at École Polytechnique. His main research interests are statistics, optimization, stochastic approximation, Federated Learning, high-dimensional learning, non-parametric statistics, and scalable kernel methods.
Jeremie Mary is a Senior Staff Researcher at Criteo AI Lab, where he focuses on reinforcement learning and image processing. He joined Criteo in 2017 and also serves as an Associate Professor at Inria (the French National Institute for Research in Digital Science and Technology). His research spans generative adversarial networks (GANs), recommender systems, and reinforcement learning.
Émilie Kaufmann is a CNRS researcher at CRIStAL, Université de Lille, and a member of the Inria team Scool. Her research focuses on statistics and machine learning, with a particular interest in sequential learning.
She studies stochastic models, particularly variants of the Multi-Armed Bandit (MAB) model, a key framework for sequential resource allocation, as well as Markov Decision Processes (MDPs). Her work spans reinforcement learning (maximizing rewards while learning) and adaptive testing (accelerating learning through adaptive data collection).
On the applied side, she is currently exploring how bandit strategies can be leveraged for adaptive early-stage clinical trials and how contextual bandits can support precision medicine.
Solenne Gaucher is an Assistant Professor in Machine Learning and Fair AI at École Polytechnique. Before that, she was a postdoctoral researcher at ENSAE, working in the FairPlay group under the supervision of Vianney Perchet.
Her research focuses on sequential learning and sequential decision-making problems, with a particular interest in fair machine learning.
Industry Round Table
July 7, 2025 | 8:45 AM – 10:30 AM
The Industry round table is composed of representatives from Hi! PARIS Corporate Donors. This event is an opportunity for the audience to learn about AI & Data Science initiatives being taken by each of the participating companies.
After an opening introduction by the panel moderators, each of the industry panel members will be invited to provide a 5-minute presentation. This will be followed by a jointly moderated session to identify areas of practical interest that can spawn impactful research. The audience will have the opportunity to ask their questions to the panelists. The industry panel will be an interactive event with an opportunity to open communication channels for further research opportunities between the industry and academia.
Poster Session & Poster Award
Posters will be displayed in Ecole polytechnique Campus from Poster session on Day 3 (Wednesday 9 July, 4:00-5:30pm) for presentation to Poster award on Day 4 (Thursday 10 July, 5:30-6:30pm).
An award, including a financial prize, will be given for the best poster.
Please note. Posters must be printed by your own means. There will be no printing on site.
Format. The preferred format of the poster is A0 paper, portrait mode (height : 119 cm, width : 84 cm). We will provide you with pins or with tape to hang your poster on the wall.
Guidelines. For Your Convenience, see above some guidelines for poster presentation borrowed from the ICML Conference.
There are many great guides to making accessible and inclusive talks and posters; we advise everyone to consider all the points made in the RECSYS guidelines, the ACM guide, and the W3C guide.
We would like to highlight the following items:
- Keep your posters clear, simple, and uncrowded. Use large, sans-serif fonts, with ample white space between sentences and paragraphs. Use bold for emphasis (instead of italics, underline, or capitalization), and avoid special text effects (e.g., shadows).
- Choose high contrast colors; dark text on a cream background works best.
- Avoid flashing text or graphics. For any graphics, add a brief text description of the graphic right next to it.
- Choose color schemes that can be easily identified by people with all types of color vision and do not rely on color to convey a message (see How to Design for Color Blindness and Color Universal Design for further details).
- Use examples that are understandable and respectful to a diverse, multicultural audience.
You can find an example of good poster and another example of a poor poster here: https://guides.nyu.edu/posters
Social Events
Two social events are schedules as part of the Hi! PARIS Summer school 2025:
- Day 1 (Monday 7 July, 6:00-7:00pm) – Opening welcome cocktail.
- Day 3 (Wednesday 9 July, 6:00-9:00pm) – Cocktail