Gérard BIAU

Gérard BIAU is a Professor at Sorbonne University, affiliated with the Laboratory of Probability, Statistics, and Modeling (LPSM). He serves as Director of the Sorbonne Center for Artificial Intelligence (SCAI). His research interests span statistical learning, machine learning, data analysis, and mathematical modeling, with a focus on theoretical foundations and applications in artificial intelligence.

Key research areas include random forests, neural networks, Wasserstein GANs, and physics-informed machine learning. He has contributed to advancements in convergence analysis of neural networks, optimal transport methods, and statistical methodologies for time series and treatment regimes. His work bridges theoretical computer science and applied mathematics, emphasizing interdisciplinary applications.

Notable awards include the Prix Marie-Jeanne Laurent Duhamel (2003), membership in the Institut Universitaire de France (2012–2017), and the Prix Michel-Montpetit-Inria (2018). Collaborations span international institutions like McGill University and industrial partners such as Criteo and EDF.

His research output includes foundational studies on random forests, collaborative inference, and gradient boosting, alongside recent breakthroughs in PINNs and Wasserstein-based learning. Industrial partnerships highlight practical applications of his theoretical work in real-world scenarios.