My research interests are in developing and analyzing estimation, inference, and optimization tools for structured high-dimensional data problems such as sparse regression, sparse nonparametric models, and low-rank models. I work on developing methods for false discovery rate control in settings where we may have undersampled data or misspecified models, and for distribution-free inference in settings where the data distribution is unknown. I also collaborate on modeling and optimization problems in image reconstruction for medical imaging.
I am a Professor in the Department of Statistics at the University of Chicago. Before starting at U of C, I was a NSF postdoctoral fellow during 2012-13 in the Department of Statistics at Stanford University, supervised by Emmanuel Candès. I received my PhD in Statistics at the University of Chicago in 2012, advised by Mathias Drton and Nati Srebro, and a MS in Mathematics at the University of Chicago in 2009. Prior to graduate school, I was a mathematics teacher at the Park School of Baltimore from 2005 to 2007, and received an ScB in Mathematics from Brown University in 2005.
Photo by Erielle Bakkum Photography.