Research Interests
My main area of research interest is the development of Bayesian methodology for the analysis of modern, complex datasets. I am particularly interested in the development of computational methods to address these problems, with recent focus on the use of parallel computing in statistics.
Specific methodological research areas include the problems of variable selection and model uncertainty in contexts of regression, prediction and complex multivariate modeling with many variables. A key element of this research is the development of stochastic search and MCMC methods for exploring large model spaces.
Links to Research Activities
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High-Dimensional Regression Modeling via Distributed Computing
National Science Foundation grant DMS-0706948
(2007-2010)