Evolutionary genetics | Bioinformatics | Ecological Genomics
Convergent and parallel evolution is among the strongest evidence for the power of natural selection, yet the mechanisms that promote repeated evolution remain poorly understood. My research integrates evolutionary genetics, population genomics, and bioinformatics to understand how organisms adapt to novel environments. Using evolve-and-resequence experiments, comparative genomics, and computational approaches, I investigate the genomic basis of parallel adaptation in both macro- and microorganisms, including how balancing selection and epistasis promote parallel genomic responses, and how cave-adapted organisms repeatedly lose complex traits like vision. My goal is to uncover generalizable mechanisms of adaptation to enable effective prediction of evolution in changing environments.
Much of my recent work involves developing bioinformatics tools for biosurveillance and bioforensics. This includes population genetics from complex samples, characterizing novel genomic elements, and large-scale whole-genome phylogenetics. Current interests include developing methods to benchmark protein structure-based phylogeny inference, using genomic foundation models to detect anomalous sequence in genome assemblies, and benchmarking scientific reasoning in AI systems.
Bioinformatics Principal Investigator — National Biodefense Analysis and Countermeasures Center (NBACC)
Professorial Lecturer — George Washington University Milken Institute of Public Health
Computational Biologist — NIAID Bioinformatics and Computational Biosciences Branch (BCBB)
NIH/NHGRI Postdoctoral Fellow — University of Wisconsin-Madison, Lee Lab
PhD, Biological Sciences — George Washington University Computational Biology Institute