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 have also served in biostatistical collaborations with the Bill & Melinda Gates Foundation and the Kaiser Permanente Division of Research.

My research interests primarily concern the development of robust and efficient statistical methodologies that lie at the intersection of causal inference and statistical machine learning, with the aim of facilitating flexible estimation and inference for complex data from observational studies or randomized trials. My interests further span nonparametric estimation, high-dimensional inference, targeted learning, statistical computing, survival analysis, and computational biology. A few recent methodological interests have included stochastic treatment regimes, causal mediation analysis, robust inference with two-phase sampling, variance moderation of semiparametric estimators, and nonparametric conditional density estimation. I am also quite interested in the design of open source software and the use of automated testing practices for the promotion of reproducible applied statistics and replicable science.