News

Research

I use mathematics and computational techniques to answer questions in evolutionary genetics. The mathematics is mostly Bayesian inference and stochastic process modeling. The computation is primarily Markov chain Monte Carlo (MCMC). The evolutionary genetics has focused on phylogenetics and multiple sequence alignment, but recently includes some population genetics and coalescent theory as well.

Work

During 2024, I'm working with Xiang Ji as a (remote) Research Scientist at Tulane University. I'm working with Xiang to add action-based likelihood computation to the BEAGLE library for GPU computation of phylogenetic likelihoods. This extension will be helpful for large-state-space substitution models.

Starting in August 2024, I am also working to assess the evolution of open source ecosystem around RevBayes. This is funded by a 1-year NSF POSE grant with Tracy Heath, Michael Landis, Jeremy Brown, and I as co-PIs.

Phylogenetic Alignment

I develop the MCMC software BAli-Phy for inferring highly-accurate multiple sequence alignments (MSA). BAli-Phy performs inference under a phylogenetic model, and so it places insertions and deletions on specific branches of the evolutionary tree instead of just placing gaps in a matrix. BAli-Phy also co-estimates the evolutionary tree along with the alignment.

Fixed-Alignment Phylogenetic Inference

I've also been contributing to RevBayes, a general program for Bayesian phylogenetic inference.