I am a fourth year PhD student at Tulane University, working with Prof. Jihun Hamm. My current research is related to understanding the robustness of machine learning under distribution shifts. I also work on developing methods for solving large-scale bilevel optimization problems that appear in popular machine learning such as hyperparameter optimization, few-shot learning, importance learning and training-data poisoning.

Previously, I have completed my Masters in Computer Science from The Ohio State University under the guidance of Prof. Jihun Hamm and Prof. Mikhail Belkin where I worked on active learning and semi-supervised learning problems.

Research Interest

To deepen the understanding of robustness of machine learning models to different types of distribution shifts such as shifts induced by corrupted data, shifts induced by adversarial attacks, etc..