François Portier is a lecturer in the LTCI S2A team at Télécom Paris. His PhD at Université de Rennes 1 was on parsimonious predictive models. He was then an FNRS postdoc at Université catholique de Louvain, where he studied certain survival analysis models. His current research work is on sequential Monte-Carlo methods, machine learning for censored and dependent data and parsimonious predictive models.
Keywords: adaptive sampling, MCMC, bootstrap, Markov chain, dimensionality reduction, survival analysis.