Professor V. Radu Craiu is a distinguished faculty member in the Department of Statistical Sciences within the Faculty of Arts and Science at the University of Toronto. He has served as Chair of the Department for 5 years (2018-2022 and 2023-2024) after joining as an Assistant Professor in 2001, being promoted to Associate Professor in 2006 and to Full Professor in 2013. Ph.D. in Statistics (2001) - University of Chicago M.S. in Mathematics (1996) - University of Bucharest B.S. in Mathematics (1995) - University of Bucharest Professor Craiu's research spans multiple domains of statistics with particular expertise in computational methods. His work has evolved from foundational research on Markov chain Monte Carlo samplers to broader applications in Bayesian statistics, copula models, statistical genetics, and more recently, astronomy. His research demonstrates both theoretical depth and practical applications across diverse fields including genetics, ecology, and astrophysics. His recent publications show a strong focus on advancing computational methodologies while addressing complex real-world problems. The research trends reveal increasing interdisciplinary collaboration, particularly with astronomers working on radio transients and stellar flares, while maintaining strong contributions to core statistical methodology in areas like copula modeling, MCMC algorithms, and dimension reduction. Fellow of the American Statistical Association (2022) Fellow of the Institute of Mathematical Statistics (2020) Faculty Affiliate of the Vector Institute (2020) CJS Award for 'Likelihood Inflating Sampling Algorithm' (2019) CRM-SSC prize from Centre de Recherches Mathematiques and Statistical Society of Canada (2016) Elected Member of the International Statistical Institute (2015) Professor Craiu has supervised numerous doctoral students whose work spans statistical genetics, computational methods, and copula modeling. His editorial service includes positions as Contributing Editor for the IMS Bulletin and Associate Editor for multiple prestigious journals including Harvard Data Science Review, Journal of Computational and Graphical Statistics, Statistics Surveys, The Canadian Journal of Statistics, and Statistical Methods and Applications. His research has been supported by various grants that have enabled extensive collaborations across disciplines.
