I am a Ph.D. student in the Group in Biostatistics at UC Berkeley. I am supervised jointly by Mark van der Laan and Alan Hubbard. Currently, I am a fellow of the UC Berkeley Biomedical Big Data training program. My research centers upon robust causal inference, nonparametric estimation and machine learning, and statistical computing. The primary focus of my work is the development of robust techniques for both estimation and inference in an eclectic collection of problem settings, with applications frequently arising from precision medicine, computational biology, and public policy. My interests are rather broad, including aspects of causal inference, censored data models and semiparametric theory, survival analysis, data-adaptive inference, nonparametric estimation and hypothesis testing, machine learning and optimization, and targeted maximum likelihood estimation. If you like any of these, we can probably find something interesting to chat about.
Ph.D. - Biostatistics, 2016-present
University of California, Berkeley
M.A. - Biostatistics, 2017
University of California, Berkeley
B.A. - Molecular & Cell Biology, Psychology, and Public Health, 2015
University of California, Berkeley
(see CV for a full list)
(see CV for a full list)