Hi! I am a second-year PhD student in Machine Learning at Carnegie Mellon University. I am advised by Zico Kolter and Aditi Raghunathan . I completed my 5th year Master’s at UC Berkeley advised by Yi Ma. Previously, I received my B.S. in Electrical Engineering and Computer Science at UC Berkeley with a minor in Bioengineering.
I am broadly interested in theoretical machine learning, nonconvex optimization, and their applications to genetics and healthcare. Currently, my research focuses on out-of-distribution generalization. Specifically, I want to better understand distribution shifts that occur in the wild and design ways to assess/improve the model’s performance under such shifts with limited labeled data. I am also interested in investigating how models can be optimized to continuously adapt to new information.
Last updated Oct 17, 2022