Research

Alain Oliviero Durmus: Rethinking generative AI from the ground up

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.

Non classé

36 Hi! PARIS Papers Accepted at NeurIPS 2025

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.

Highlight Research
Solenne Gaucher

Why ignoring sensitive Data doesn’t make AI fair

At this year’s Hi! PARIS Summer School, Solenne Gaucher (École polytechnique) shed light on the growing challenge of fairness in AI. As algorithms trained on biased data shape decisions at scale, she reminded us that fairness is neither only a mathematical problem nor only an ethical one. Instead, it sits at the intersection of both, and demands attention from scientists, policymakers, and society alike.