I have done extensive work in the development of Bayesian hierarchical models, elicited prior development from expert interviews,as well in fundamental issues in statistical inference. I have extensive expertise in statistical computing, Markov chain Monte Carlo (MCMC) tools in particular. Most sophisticated Bayesian models for the social or medical sciences require complex, compute-intensive tools such as MCMC to efficiently estimate parameters of interest. I am an expert these statistical and computational techniques and use them to contribute to empirical knowledge in the biomedical and social sciences. Current theoretical work builds logically on my prior applied work and adds opportunities to develop new hybrid algorithms for statistical estimation with multilevel specifications and complex time-series and spatial relationships. Current applied work  includes: blood and circulation, long-term mental health outcomes from children’s exposure to war, pediatric head trauma, terrorism studies, and trauma physiology, and political economy of the states.