Summary
Pierre-henri Wuillemin is an assistant professor (Maître de Conférence) based in Paris with 17 years of experience at the intersection of AI, applied mathematics, statistics, and software development. His research focuses on Bayesian networks, spanning theoretical advances in inference and structure/parameter learning as well as practical applications like object-oriented modeling, troubleshooting, and (PO)MDPs. He combines rigorous academic work with hands-on software craftsmanship, building frameworks that make complex probabilistic models more reusable and maintainable. Known for improving inference algorithms, he bridges methodological innovation and applied systems that support decision-making under uncertainty. Operating from LIP6 (UPMC) since 2003, he brings deep institutional experience and continuity in both teaching and research. Colleagues describe him as someone who turns abstract probabilistic theory into pragmatic tools for real-world AI problems.
17 years of coding experience
English, French