I am broadly interested in the mechanisms of molecular evolution and in how they can be better inferred from large, densely-sampled phylogenomic and population-genomic datasets.

My current work is focused on modeling and inference of complex patterns of protein evolution and co-evolution from large comparative genomic data sets using novel data augmentation strategies and Markov-Chain Monte Carlo (MCMC).  I have also worked on improving likelihood-based approaches for detecting episodic molecular adaptation, sequence convergence, and on asymptotic methods for objective experimental design.  My doctoral work was largely focused on making better functional inferences along short evolutionary lineages (details forthcoming).

Doctoral dissertation: “Experimental Design and the Detection of Adaptive Molecular Divergence in Phylogenetics and Genomics.” (2007)  Thesis advisor: Caro-Beth Stewart