I am an associate professor in the Department of Statistics, and an affiliated faculty in the Machine Learning Department, at Carnegie Mellon University. I graduated from Stanford University in 2007 with a B.S. in mathematics, and a minor in computer science. By the end of my time as a graduate, I realized that statistics really offered the best of both worlds! I graduated with a Ph.D. in statistics from Stanford University in 2011, with Jonathan Taylor as my advisor. In the fall of 2011, I joined the faculty of statistics at Carnegie Mellon University as an assistant professor.
My research is focused on statistical machine learning, from both the applied and theoretical perspectives. My interests also include model selection, describing and understanding model complexity, cross-validation and resampling methods, convex optimization and geometry, and the statistics of sports and games. Some of my recent work described degrees of freedom in lasso problems, and derived a path algorithm for the generalized lasso. And if that sounds boring to you: I have also worked on optimal strategies for playing darts!