Vicky Kalogeiton, Hi! PARIS Fellow, has been awarded the 2026 CNRS Bronze Medal, recognizing her contributions at the intersection of computer vision, multimodal analysis, and generative artificial intelligence. Currently a […]
Anna Korba receives the 2026 Bronze Medal of the CNRS for her contributions at the intersection of mathematics, statistics, and artificial intelligence, advancing key methods in sampling and generative models.
For 2026, we are welcoming eleven international visiting professors. Each will collaborate on a specific project in artificial intelligence or data science, hosted by a Hi! PARIS researcher.
At the Collège de France, researchers ask what kind of AI ecosystem research can sustain One year after the AI Action Summit, the question is no longer whether artificial intelligence […]
As part of the Hi! PARIS Initiatives, this Meet Up on “AI & the Future of Work” will bring researchers, industry leaders, and practitioners together at Station F. The goal: to reflect on how AI is reshaping jobs, skills, and workplace dynamics, and to explore what this transformation means for companies, policymakers, and society.
Schneider Electric has renewed its partnership with Hi! PARIS for three additional years, reinforcing a shared commitment to advance open and responsible AI. This new phase will support cutting-edge research, launch a new chair on AI and energy, and expand opportunities for students and doctoral candidates across the center.
Artificial intelligence has mastered language, vision, and even strategy games, but can it master mathematics? Amaury Hayat’s DESCARTES project explores one of the boldest frontiers in science: teaching machines not just to calculate, but to reason.
While generative AI tools continue to impress, their inner workings remain largely mysterious. Hi! PARIS Fellow Alain Oliviero Durmus is tackling this challenge head-on with his project TODO – Toward Enhanced Generative Models. By applying tools from stochastic optimal control, he’s building a stronger mathematical foundation for diffusion and flow models, aiming to make them more robust, interpretable, and ready for complex real-world applications.
Every measurement, whether in physics, statistics, or machine learning, comes with a cost. From Heisenberg’s uncertainty principle to the limits of data prediction, Professor Xiao-Li Meng reminds us that knowledge itself is bounded by trade-offs. Precision and uncertainty are not opposites, they are partners in the same dance. In science, as in life, there is no free lunch.
This year, 36 papers from Hi! PARIS affiliated researchers have been accepted at NeurIPS 2025, one of the world’s most prestigious conferences in artificial intelligence and machine learning., highlighting the strength and breadth of our research across partner institutions.
A strong showing that reflects our continued commitment to advancing the frontiers of AI for science, business, and society.