Research Interests

Bayesian statistical methodology motivated by complex biomedical data. Ongoing methodologic research focuses on nonparametric Bayes, latent variable methods, variable and covariance selection, semiparametric methods for density and quantile regression, and order restricted inference. A particular focus has been on developing flexible methods for hierarchical modeling, which allow latent variable distributions to change nonparametrically with multiple predictors. This research has been motivated by molecular epidemiology and bioinformatics studies, but has broad applications. Related work focuses on developing methods for selection of random effects in generalized linear mixed models, avoiding parametric assumptions on the random effects distributions. Methodologic work is strongly motivated by real world applications, including (but not limited to) studies of human fertility, reproductive epidemiology, toxicology, and (recently) genetic and environmental factors predictive of DNA damage and repair. Genetic studies has been an increasing focus.

Postdoctoral Fellow Position

Recent Publications.

Submitted Manuscripts.

Course Webpage: STA216: Generalized Linear Models

Recent Awards: 2007 Fellow of the American Statistical Association

2007 Spiegelman Award for top biostatistician under 40

2007 Gold Medal for exceptional service from EPA

Latest painting

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