Biography
I am a PhD student in Biostatistics and a member of the Center for Computational Biology’s designated emphasis program in computational and genomic biology at UC Berkeley. I am advised jointly by Mark van der Laan and Alan Hubbard, and I am lucky to also work under the supportive guidance of David Benkeser and Nicholas Jewell. My research interests are a bit eclectic, spanning causal inference, nonparametric estimation (i.e., machine learning) and inference, targeted loss-based estimation, survival analysis and censored data models, statistical computing and reproducible research, and computational biology. My work is primarily driven by nonparametric estimation of quantities from causal inference, motivated by and applied to pressing scientific and policy problems. Most recently, substantive applications have included vaccine efficacy trials, precision medicine, and public policy (e.g., algorithmic fairness).
Interests
- Causal Inference
- Machine Learning
- Targeted Loss-Based Estimation
- Nonparametric Statistics
- Semiparametric Theory
- Statistical Computing
- Reproducible Research
- Computational Biology
- Survival Analysis
- Data Science
Education
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PhD in Biostatistics, with a designated emphasis in Computational & Genomic Biology, 2016-present
University of California, Berkeley
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MA in Biostatistics, 2017
University of California, Berkeley
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BA with a triple major in Molecular & Cell Biology, Psychology, and Public Health, 2015
University of California, Berkeley