I began as a cellist before adding musician, economist, and now statistician to my list of professions. I believe that, in order to address really interesting problems, one needs to be able to understand how to develop appropriate statistical methodology and justify its use.
I work on applications of statistical machine learning. Most of my work involves providing theoretical justification for existing methodology. I am also interested in computational approximations; time series; and applications in economics, climate science, and chemistry. My work is partially supported by an NSF CAREER Award.
Statistics is about combining careful data analysis with scientific expertise to solve significant problems. Given the quantity of data available today, students need to thoroughly understand how to communicate and justify statistical conclusions to scientists, researchers, and policy makers.