Consider the following remarkable existence problem: there exists a Canadian statistician, part-time comedian, musician, born on Friday the thirteenth during the Canadian Centennial, who is quoted in the New York Times, who has appeared in Cadbury milk chocolate commercials, on William Shatner’s television program “Weird or What?”, on CBC television’s “The Fifth Estate”, and whose day job involves winning awards both for research and teaching and writing best-selling books.
 
Professor Jeffrey Rosenthal, of the Department of Statistics at the University of Toronto, demonstrates the existence of a solution to this problem, and his monumental achievements seem to guarantee uniqueness for decades to come. The son of mathematical parents in Scarborough, Ontario, Jeffrey graduated from Woburn Collegiate in 1984, from the BSc program in Mathematics, Physics and Computer Science at the University of Toronto in 1988, and with a PhD in Mathematics from Harvard University under the supervision of Persi Diaconis in 1992.
 
Since 1993, Jeff has been on faculty in the Department of Statistics at the University of Toronto. His research areas are probability theory, stochastic processes, and Markov chain Monte Carlo (MCMC) algorithms, with applications to statistics and to interdisciplinary applications of statistics. His research has had a profound influence on the fields of probability and statistics, and his writings and many public appearances on the public understanding of probability and its applications. He has made fundamental contributions to the Markov chain theory and to the convergence analysis of Markov chain Monte Carlo algorithms. His introduction of the “minorization conditions” in his influential 1993 JASA publication has a far-reaching impact and is widely cited. Jeff’s exemplifications of how to obtain a practical convergence, found in both this 1993 JASA and his 1992 Annals of Statistics articles, have become a standard practice for researchers to prove convergence of a MCMC algorithm. Jeff’s research interest is extremely broad and his contributions also range broadly, including slice sampler, convergence diagnostics, exact/perfect sampling, MCMC algorithm design, regeneration, and adaptive MCMC. A central theme of Jeff’s contribution is to obtain practical and useful theoretical results, for example accurate quantitative bounds, conditions for geometric convergence, practical perfect sampling, etc.
 
Jeff was named a Fellow of the Institute of Mathematical Statistics in 2005, received the CRM-SSC prize in 2006, and in 2007 was awarded the prestigious Presidents’ Award from the Committee of Presidents of Statistical Societies (COPSS award). He was elected to Fellowship of the Royal Society of Canada in 2012. Jeff’s book for the general public, Struck by Lightning: The Curious World of Probabilities, is being published in sixteen editions and ten languages, and was a bestseller in Canada. It led to numerous media and public appearances. Jeff has also published two textbooks about probability theory, and over ninety refereed research papers.
 
Jeff has contributed to probability and statistics in Canada and internationally in every corner of the spectrum, from the mathematical depth of his research in probability, his attention to applications, to the public understanding of risk and the role of probability and statistics in everyday life.