WELCOME
I am a statistician interested in the development and application of Bayesian methodology and thinking to data analytic problems from across the social and biological sciences. I spent the 2011 - 2012 year as a Post-Doctoral Research Associate under the guidance of the late George Casella at the University of Florida and I am currently being supervised by Linda Young. Sergey Nuzhdin of Molecular and Cellular Biology as well as David Conti, Paul Marjoram, and Duncan Thomas of Biostatistics at USC have generously agreed to house and mentor me while I further the research agenda I started with Dr. Casella. I graduated from Washington University in St. Louis in 2011 with a Ph.D. in Mathematics under the guidance of Jeff Gill.
I am interested in the application of Bayesian methods to problems of model selection. My research projects include: investigating the development of intrinsic priors across a variety of problems and studying their frequentist properties, developing consistent priors for topic selection in latent allocation models, and model based clustering. These projects are all motivated by problems in the social and biological sciences.
In the social sciences, I am interested in ways to model the structure of observed and unobserved heterogeneity that pervades social data. This heterogeniety comes coupled with temporal and spatial correlations between observations that often makes analysis difficult. I am involved in projects looking at American and international institutional variation and its effect on polticial actors.
I also have a growing interest in the application of model selection in "p>n" problems such as arise in genetic studies. In addition to applications of intrinsic methodologies to these problems, I am also interested in informative prior specifications that take into account structure in the model space. I am currently involved in a project using genetic pathways with researchers in biostatistics.