Dr. Bédard’s thesis is entitled “On the Robustness of Optimal Scaling for Random Walk Metropolis Algorithms” and was completed at the University of Toronto under the supervision of Professor Jeffrey Rosenthal. The thesis used sophisticated probabilistic arguments to establish optimal implementations of the Metropolis-Hastings algorithm for Markov chain Monte Carlo. The Metropolis-Hastings algorithm is one of the most widely used methods in modern Bayesian analysis, with applications ranging throughout the sciences. Dr. Bédard’s results have extended previous work on optimal implementations to increasingly realistic settings and thereby further extended the scope of this powerful algorithm.
 

Dr. Bédard received her B.Sc. from the Université Laval in 2001 before moving to Toronto, where she receivedher M.Sc. in 2002 and Ph.D. in 2006. She is now a research fellow working within the Centre for Research in Statistical Methodology at the University of Warwick in Coventry, England. She will soon join the Département de mathématiques et de statistique at the Université de Montréal, where she has been appointed Assistant Professor. There, she will continue her work on the Metropolis-Hastings algorithm and Markov chain Monte Carlo methods in general.
 

The criteria used in the assessment of theses for this award include the originality of ideas and techniques, the possible applications and their treatment, and the potential impact of the work on the statistical sciences. The award is named in memory of Professor Pierre Robillard, an outstanding dynamic young statistician at the Université de Montréal, whose untimely death in 1975 cut short what promised to be a highly distinguished career in statistics.