I am currently a Data Scientist in the Faculty of Arts and Sciences Informatics Group at Harvard University and a Senior Research Fellow in the Center for Tropical Research at University of California, Los Angeles. In practice, I’m an evolutionary genomics scientist and bioinformatician conducting research on a variety of evolutionary questions and statistical methods for genome-scale data analysis. I also provide consulting services to graduate students, postdoctoral researchers, and primary investigators in the Harvard scientific community, with respect to study design and data analysis of high throughput sequencing experiments. A necessary extension of this work, I’m a programmer writing (primarily python) code to build tools for analyzing genomic data and automating complex workflows.

I hold B.A. and B.S. degrees in Philosophy and Environmental Science, respectively, as well as an M.S. in Wildlife Ecology and Conservation. I completed my PhD at University of California, Los Angeles in 2009, working with Tom Smith on diversification of African rainforest lizards and birds, as well the ecological and evolutionary impacts of deforestation. Subsequent to my PhD, I was awarded a National Science Foundation Postdoctoral Fellowship in Bioinformatics, during which I worked with John Novembre at UCLA (now at University of Chicago) on dog domestication genomics. For my second postdoc, I worked with Hopi Hoekstra and Jonathan Losos (Harvard University) and Chris Schneider (Boston University) on the genetic architecture of dewlap pigmentation in Anolis lizards. I started as a Data Scientist at Harvard in June of 2015.

At various times, my research has been funded by the U.S. Environmental Protection Agency, the National Science Foundation, and the Fulbright Foundation.

Last but not least, I am the owner of a very small farm in central Massachusetts, and am a rarely performing purveyor of sad songs, having the perhaps not too rare distinction of accidentally using profane language while playing live on an NPR affiliate during rush hour.