I am a post-doc in the Department of Statistics. Motivated by data sets with interesting phenomena, but few variables to describe or explain the phenomena, I work to develop, fit, and understand the statistical properties of Bayesian models. Currently, I am working with Prof. Abel Rodriguez on creating and implementing circular models to better represent the ideological positions of politicians and judges.

Before coming to the University of Washington, I earned Ph.D. at the University of Michigan with Professor Long Nguyen as my advisor. My projects there included building models to transform data on simplexes in order to model changes in neighborhood income proportions and designing algorithms to fit tree-based mixtures of topic models.