Robert Tibshirani is a Professor in the Departments of Statistics and Biomedical Data Sciences at Stanford University In his work he has made important contributions to the analysis of complex datasets, most recently in genomics and proteomics. Some of his most well-known contributions are the lasso, which uses L1 penalization in regression and related problems, generalized additive models and Significance Analysis of Microarrays (SAM). He also co-authored four widely used books "Generalized Additive Models", "An Introduction to the Bootstrap", "The Elements of Statistical Learning", and "Sparsity in Statistics: the Lasso and its generalizations.
How many units of platelets will the Stanford Hospital need tomorrow?
Professor Rob will discuss a system based on a novel form of supervised learning for predicting the number of units that will be needed daily by Stanford Hospital.