Biography

I am a PhD candidate in biostatistics, with a designated emphasis in computational and genomic biology, working with Mark van der Laan and Alan Hubbard. I am a founding core developer of the tlverse, the software ecosystem for targeted learning, and a workshop instructor with Software Carpentry. At UC Berkeley, I am affiliated with the Center for Computational Biology and the NIH Biomedical Big Data initiative. I also serve on biostatistical collaborations with the Bill & Melinda Gates Foundation and the Kaiser Permanente Division of Research.

My research interests fall in nonparametric causal inference, machine learning and data adaptive estimation, computational biology, survival analysis, and statistical computing. My recent methodological interests have included stochastic treatment regimes, causal mediation analysis, robust inference under two-phase sampling, locally efficient variance moderation, and nonparametric conditional density estimation. Thus far, my work has been primarily motivated by applications to vaccine efficacy trials, massive electronic health records data, epigenetics and genomics, and large-scale field epidemiology. I am also quite keenly interested in software development for applied statistics, including open source software, automated testing, and reproducible research.