My research addresses fundamental questions in contemporary population genomics: the study of an organism's entire complement of DNA. I have particular interest in modeling genome dynamics — firstly, establishing how genetic variation is distributed within and between individual genomes, and secondly, determining how this diversity changes over evolutionary time.
My work draws heavily on statistics and computer science with a solid foundation in genetics and biochemistry. I develop computational methods for genome analysis, such as establishing analytical pipelines for second-generation sequencing technologies. I also design and implement novel algorithms and statistics, largely in the fields of coalescent theory, demographic inference and systems biology. I am currently applying these tools to a series of ongoing projects, which includes using neutral genomic variation to reconstruct the demographic history of humans, linking global patterns of diversity to evolutionary dynamics in small subpopulations, and advancing studies of non-model organisms through de novo genome sequencing and automated gene analysis.
More broadly, I am interested in the interface between biology, statistics and computer science, especially where large genetic datasets can be applied to address questions of outstanding biological importance.
