Thursday, November 17, 2016
James Francis Hannan Visiting Scholars Series
(Conferences / Seminars / Lectures)
We are honored to have internationally renowned statistician Professor Peter Bühlmann, ETH, Zurich, visiting the MSU Department of Statistics and Probability as a James Francis Hannan Visiting Scholar, for the week of November 12 to 18, 2016. more information...
James Hannan was a founding faculty member of the Department of Statistics and Probability at MSU (1953-2002). Jim published important and novel findings in statistics and game theory, and directed or co-directed twenty graduate students to their PhD's. The James Francis Hannan Visiting Scholar Program was established to honor Jim by the generous support from his wife Bettie Hannan.
Peter Bühlmann is Professor of Mathematics and Statistics, and currently Chair of the Department of Mathematics at ETH Zurich. He studied mathematics at ETH Zurich and received his doctoral degree in 1993 from the same institution. He was a Postdoctoral Research Fellow in 1994-1995 and a Neyman Assistant Professor from 1995-1997 at UC Berkeley.
Professor Peter Bühlmann, ETH, Zurich will cover Inhomogenous Large-Scale Data: New Opportunities for Causal Inference and Prediction.
Abstract: Large-scale or "big" data usually refers to scenarios with potentially very many variables (large
dimension) and large sample size. Such data is most often of "inhomogeneous" nature, i.e.,
neither being random samples from a common population nor being generated from a
stationary distribution. We discuss how to exploit the advantage of heterogeneity in large
datasets. A key ingredient is an invariance principle that leads to new approaches for causal
inference and novel prediction methods, which exhibit "robustness" even for scenarios not
present in the observed data. As a concrete application, we discuss large-scale gene knockdown
experiments in yeast (Saccharomyces Cerevisiae) where computational and statistical
methods have an interesting potential for prediction and prioritization of new experimental