Robert Tibshirani is a Professor in the Departments of Statistics and Health Research and Policy at Stanford University, internationally known for his work in data mining and applied statistics. He develops statistical tools and makes exceptional contributions to methodology and theory for the analysis of complex data sets, for smoothing and regression methodology, in statistical learning and classification, and in application areas that include public health, genomics, and proteomics. His impact has spanned decades, from his thesis work on local likelihood estimation, to his development of and continuing work with his well-known LASSO method, which uses an L1 penalization in regression and related problems. Another important contribution is his work on Significance Analysis of Microarrays. He has also co-authored three well-known books: "Generalized Additive Models", "An Introduction to the Bootstrap", and "The Elements of Statistical Learning”. The last book has become one of the classic texts in data mining. Prof. Tibshirani has received numerous honors and awards for his great contributions, including the 1996 COPSS Presidents' Award and 2012 Statisticial Society of Canada's Gold Medal. He is a Fellow of the Institute of Mathematical Statistics, the American Statistical Association, and the Royal Society of Canada, and a member of the U.S. National Academy of Sciences. This event is jointly supported by the Prof. Constance van Eeden (http://www.stat.ubc.ca/Department/CvE.php), Department of Statistics and PIMS (https://www.pims.math.ca/). Title and abstract of presentation will be forthcoming.