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Keynote Session 2
Title: Bayesian Magic
Dr. David Madigan
Professor, Northeastern University
Bio: Professor David Madigan is the Provost and Senior Vice President for Academic Affairs at Northeastern University, where he is also a Professor of Statistics. Previously he served as Executive Vice President of Arts and Sciences and Dean of the Faculty at Columbia University, and as Chair of Columbia’s Department of Statistics. He has also held positions at AT&T Inc., Rutgers University, and the University of Washington.
His research spans Bayesian statistics, text mining, Monte Carlo methods, pharmacovigilance, and probabilistic graphical models. He holds a B.Sc. in Mathematical Sciences and a Ph.D. in Statistics from Trinity College Dublin. He is a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the AAAS, and has served as Editor-in-Chief of Statistical Science.
Abstract
The Bayesian approach to data analysis has become routine and the fierce Bayesian-frequentist debates of old have fizzled out. Authors have often lauded the simplicity and interpretability of the Bayesian approach and this has proven to be compelling in countless real-world applications. There are, however, some contexts in which Bayesian thinking provides extraordinary advantages - Bayesian magic if you will. I will describe three such contexts in some detail - zero-profiling for location estimation in wireless networks, automated informative priors in text categorization, and hierarchical association rule mining in healthcare.
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