Dr. Demer is a Statistician in the UCLA Statistics Core. His interests include quantitative aspects of study design, and finding Bayesian priors with a reduced dimension of improperness to allow comparisons of models in situations where, for standard improper priors, the posteriors would depend on the order of updates.