Nicolas Chopin is Professor of Data Science, Statistics, and Machine Learning at ENSAE Paris. He is also a Hi! PARIS Fellow for the 2026-2029 period.

His research focuses on Bayesian computation and the development of algorithms for Bayesian inference. He works on Monte Carlo methods, with a particular interest in Sequential Monte Carlo, as well as Markov chain Monte Carlo, quasi-Monte Carlo, and related approaches. He also studies fast approximation methods for Bayesian inference, including Expectation Propagation and variational Bayes.