We work at the intersection of statistical genetics, population genetics, and machine learning. We primarily develop methods and theory to understand how evolution shapes the genetic architecture of complex traits at different biological scales, with the hope of leveraging these insights to better interpret and use genome-wide association tests and rare variant burden tests.  More broadly, we are interested in any biological puzzle that presents interesting computational or statistical challenges.