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PRODID:-//Virginia Tech//VT Calendar//EN
BEGIN:VEVENT
DTSTAMP:20161117T200000Z
UID:1478278702276@events.msu.edu
CATEGORIES:Conferences / Seminars / Lectures
DTSTART:20161117T200000Z
DTEND:20161117T205000Z
SUMMARY:James Francis Hannan Visiting Scholars Series 
DESCRIPTION:
 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. \n
 \n
 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.\n
 \n
 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.  \n
 \n
 Professor 
 Peter Bühlmann, ETH, Zurich will cover 
 Inhomogenous Large-Scale Data: New Opportunities 
 for Causal Inference and Prediction. \n
 \n
 Abstract: 
 Large-scale or "big" data usually 
 refers to scenarios with potentially very many 
 variables (large\n
 dimension) and large sample 
 size. Such data is most often of "inhomogeneous" 
 nature, i.e.,\n
 neither being random samples 
 from a common population nor being generated 
 from a\n
 stationary distribution. We discuss 
 how to exploit the advantage of heterogeneity 
 in large\n
 datasets. A key ingredient is 
 an invariance principle that leads to new approaches 
 for causal\n
 inference and novel prediction 
 methods, which exhibit "robustness" even 
 for scenarios not\n
 present in the observed 
 data. As a concrete application, we discuss 
 large-scale gene knockdown\n
 experiments in yeast 
 (Saccharomyces Cerevisiae) where computational 
 and statistical\n
 methods have an interesting 
 potential for prediction and prioritization 
 of new experimental\n
 interventions.\n
 \n\n
 Price: free\n
 Sponsor: Department of Statistics and Probability\n
 Sponsor's Homepage: http://www.stt.msu.edu\n
 Contact name: Department of Statistics and Probability\n
 Contact phone: 517-355-9589\n
 Contact email: staff@stt.msu.edu\n
 for more info visit the web at:\n 
 https://stt.msu.edu/Seminars/default.aspx\n
LOCATION:B122 Wells Hall
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