Short bio
Professor at Université Paris Dauphine since 2000, part-time professor at University of Warwick (Fall 2013- ), fellow of the ASA (2012) and the IMS (1996), former editor of the Journal of the Royal Statistical Society (2006-2010) and deputy editor of Biometrika (2018-), senior member of Institut Universitaire de France (2010-2021)
Topics of interest
Foundations of Bayesian analysis, Bayesian decision theory, Markov chain simulation methods, approximate Bayesian inference
Project in Prairie
To assess and improve approximate inference methods that handle complex and big data models, in particular developing novel ABC and MCMC technology. Contribution to the PSL maths graduate school by teaching and administrating the MASH program. Animation of international conferences and summer schools in Bayesian computational statistics.
Quote
Christian Robert travaille depuis une quinzaine d’années sur les méthodes d’inférence bayésienne approximatives, induites par la complexité ou la taille des données. Ses résultats valident des méthodes de Monte Carlo sur des modèles génératifs et aident à la construction de techniques de réduction de dimension efficaces.
Team
