As of April 2026, I am a Statistician at Genentech. I completed my PhD in Statistics at UC Berkeley in 2026, where I was advised by Haiyan Huang, Sam Pimentel, and Avi Feller. I received my B.S. in Statistics from UCLA in 2021.
My research was motivated by causal inference problems in health policy and medicine, with a focus on developing methods for robust and transparent causal inference. I continue to be actively engaged in research at the intersection of causal inference, machine learning, and survival analysis. My doctoral work was supported by the NSF Graduate Research Fellowship.
Recent News
April 2026: I have completed my PhD in Statistics at UC Berkeley and joined Genentech as a Statistician.
December 2025: Our paper on using tree-ensembles to estimate better weights for causal inference is now on arXiv!
May 2025: I started my internship at Genentech in the Product Development Data Sciences group.
May 2025: Our paper on analyzing multiple sclerosis progression with volumetric MRI has been accepted in Computational and Structural Biotechnology Journal!
February 2025: Our paper on sensitivity analysis for causal decompositions is published in Statistics in Medicine!
January 2025: Our paper on sensitivity analysis for causal decompositions received student paper awards for the 2025 International Conference on Health Policy Statistics and the 2025 Joint Statistical Meetings.