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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Second IMS-ISBA Joint Meeting
Bormio, Italy - January 2005
Regression Model Uncertainty With Very Many Predictors -
International Workshop on Bayesian Data Analysis
Santa Cruz, California - August 2003
Constructing High-Dimensional Sparse Graphical Models -
First IMS-ISBA Joint Meeting
San Juan, Puerto-Rico - July 2003
Understanding Galactic Orbits: MCMC in Highly Constrained Parameter Spaces -
Statistical Challenges in Modern Astronomy III
Penn State University - July 2001
Accounting for Absorption Lines in High Energy Spectra