Dr. François Perron

Biography

François Perron is a full professor in the Department of Mathematics and Statistics at the Université de Montréal. His research primarily focuses on the theoretical aspects of statistics, including decision theory, Bayesian approaches, multivariate statistics, and simulation methods known as Markov Chain Monte Carlo (MCMC). One of his notable projects involves developing an algorithm that creates a Markov chain with a pre-specified stationary distribution while identifying intermediate distributions at each time step. This new algorithm aims to compete with the widely used Metropolis and Hastings algorithm and generalizes the acceptance-rejection method. In his teaching roles, he supervises graduate students, guiding them through their theses and dissertations in statistical estimation and simulation methods. He has collaborated on various research projects seeking to enhance Bayesian estimation techniques and advance methods in computational statistics. His contributions significantly impact theoretical statistics and applied mathematics, particularly within actuarial studies, data mining, and stochastic processes.

Research Interests

Experience