Published numerous papers on topics such as empirical Bayes for large-scale randomized experiments, concentration of empirical probabilities in relative entropy, multiplicative effect modeling, identifying conditional path-specific effects, testing marginal versus conditional independence, and more.
Research Experience
Has extensive research experience in the fields of statistics, economics, and electrical engineering.
Education
BA from the University of Oxford; MS and PhD from Carnegie Mellon University.
Background
Professor in the Department of Statistics, also an Adjunct Professor in the Departments of Economics and Electrical Engineering, and a member of the eScience Steering Committee. His research interests include Graphical Models and Causality.