Seminar: Tim Au, Bayesian Inference for the Causal Impact of Online Advertising Using Linear Gaussian State Space Models

Speaker: Tim Au, Data Science Manager at Google

Title: Bayesian Inference for the Causal Impact of Online Advertising Using Linear Gaussian State Space Models

Abstract: 

Seminar: Yaqing Chen, Geometric Exploration of Random Objects Through Optimal Transport

Speaker: Yaqing Chen, Assistant Professor, Rutgers University

Title: Geometric Exploration of Random Objects Through Optimal Transport

Seminar: Po-Ling Loh, Robust empirical risk minimization via Newton's method

Speaker: Po-Ling Loh, Professor, University of Cambridge

Title: Robust empirical risk minimization via Newton's method

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Seminar: Sihai Dave Zhao, Empirical Bayes in Genomics

Speaker: Sihai Dave Zhao, Associate Professor, University of Illinois Urbana-Champaign

Title: Empirical Bayes in Genomics

Abstract: Empirical Bayes methods have a long history in statistics and have become especially popular for large-scale inference. This talk describes some new applications of these idea to problems motivated by genomics, including coexpression network reconstruction and large-scale gene expression imputation. At the same time, the philosophy of empirical Bayes has always been a bit mysterious, and this talk also investigates a fully frequentist perspective on modern results.

Seminar: Ruth Pfeiffer, Building and Validating Risk Models for Clinical and Public Health Applications

Speaker: Ruth Pfeiffer, Senior Investigator, National Cancer Institute

Title: Building and Validating Risk Models for Clinical and Public Health Applications

Seminar: William Brenneman, The Interplay between Statistical Practice and Academic Research

Speaker: William Brenneman, Retired Research Fellow and Global Statistics Discipline Leader, Procter & Gamble Company

Title: The Interplay between Statistical Practice and Academic Research

Abstract: In the statistics field, there is a strong symbiotic relationship between academics and industry.  We will explore this relationship primarily from a practicing statisticians’ perspective and discuss the lessons learned on how to foster, grow and bridge the gap between statistical practice and academic research.  Several problems encountered in industry that led to academic research projects will be highlighted.

Seminar: Moulinath Banerjee, University of Michigan

Speaker: Moulinath Banerjee, University of Michigan

Title: TBD

Abstract: TBD

Fuller Lecture: Danny Pfeffermann, University of Southampton

Speaker: Danny Pfeffermann, University of Southampton

Title: TBD

Abstract: TBD

Pathway Seminar: Bill Meeker, Iowa State University

Speaker: Bill Meeker, Distinguished Professor, Iowa State University

Title: 

Abstract: 

Seminar: Debashis Mondal, University of Washington

Speaker: Debashis Mondal, University of Washington

Title: TBD

Abstract: TBD

Seminar: Nancy Reid, University of Toronto

Speaker: Nancy Reid, University of Toronto

Title: TBD

Abstract: TBD