High Performance Bayesian-based Phylogenetic Inference

In the computational biology area, my focus is on developing advanced computational approaches and tools to address grand challenges in understanding of biological systems and their impact on nature and human health. My dissertation research was on large scale phylogenetic inference, in which I have developed a high performance, Bayesian-based phylogenetic inference framework [1]. Part of the work has been implemented in a software package called PBPI (parallel Bayesian phylogenetic inference) [2, 3] which is over 1000 times faster than the previous best available program, reducing analysis time from several weeks down to less than one hour. This work was a best student paper finalist at the IEEE/ACM supercomputing 2006 conference.