Highlight Research

Rethinking Uncertainty in Machine Learning

As machine learning systems become embedded in critical decisions, from finance to infrastructure, the need for trustworthy, interpretable predictions has never been greater. Aymeric Dieuleveut, Professor of Statistics and Machine Learning at École polytechnique and scientific co-director of the Hi! PARIS Center, believes the key lies not in the models themselves, but in how we communicate their uncertainty.

Highlight Teaching

AI Seminar Cycle

The Hi! PARIS AI Seminar Cycle is a monthly series showcasing leading research in Artificial Intelligence and Data Science. Held on the first Wednesday of each month, it brings together top scholars, students, and partners to explore AI’s scientific, business, and societal impact across key themes such as foundation models, trustworthy AI, and AI for science and engineering.

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