I am a third-year Ph.D. student at the NYU Center for Data Science, advised by Kyunghyun Cho and Krzysztof Geras. In my research, I apply ideas from causality to improve out-of-distribution generalization in machine learning. My aim is to develop simple and effective methods that are applicable to important real-world problems such as medical diagnosis.

News
Sep. 14, 2022: “Generative multitask learning mitigates target-causing confounding” was accepted to NeurIPS 2022!