A Short Biography of Longhai Li
Longhai Li received his PhD and M.Sc degrees in statistics from the University of Toronto (U of T). His doctoral supervisor was Radford M. Neal. His math genealogy can be found from here. Before that, he received his B.Sc in statistics from the University of Science and Technology of China. He joined the Department of Mathematics and Statistics at the University of Saskatchewan (U of S) in 2007. He became a full professor in 2018. His research interest lies mainly in two areas: (1) statistical machine learning for high-throughput data; (2) diagnostics and comparison of complex statistical models. He is also broadly interested in applications of machine learning for industry problems. His research has been funded by a few national grant agencies or programs, including NSERC, CFI, CFREF, and MITACS. The journals that he has published include: Journal of American Statistical Association, Bayesian Analysis, Statistics in Medicine, Statistics and Computing, Scientific Reports, PLOS ONE, BMC Bioinformatics, and many others. A predictive model comparison method developed by him, called integrated importance sampling (iIS), is included in a widely used textbook Bayesian Hierarchical Models: With Applications Using R, 2nd edition by Peter Congdon.