Brian Cho
A page for updates on my latest projects and publications.
I’m a Ph.D student at Cornell University, broadly interested in causal inference, experimental design, and applications in high-risk domains such as healthcare and policy.
Previously, I was a research assistant for the Tobin Economics Research Program, Lawrence Berkeley National Laboratory, and Yale’s Department of Statistics and Data Science. I’ve also held interdisciplinary opportunities through the Information Society Project, and gained industry experience as an intern at Bridgewater Associates.
See my publications, code, and ongoing research projects below!
| Resume |
Works in Progress
- Kernel Debiased Plug-in Estimation (w. Kyra Gan, Ivana Malenica, Yaroslav Mukhin)
- Preprint (Finalist at INFORMS DMDA Workshop, Theoretical Track)
- Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams (w. Kyra Gan, Nathan Kallus)
Software
- distillML: Interpretable Machine Learning Methods and Surrogate Model Methods (w. T. Saarinen, S. Walter, J. Sekhon)
Workshop Proceedings
- Effective Missing Value Imputation Methods for Building Monitoring Data (w. T. Dayrit, Y. Gao, Z. Wang, A. Sim, K. Wu)