Rank-Constrained Adaptation for Reliable Real-World Performance
Abinitha Gourabathina
Abinitha is a PhD student at MIT EECS. She is co-advised by Professors Marzyeh Ghassemi and Collin Stultz. Her research interests lie broadly in trustworthy machine learning. By investigating the latent spaces and distributions of foundational models, she seeks to audit generative models in high-stakes settings like healthcare and improve model performance for safety-driven goals. She completed her B.S.E. in Operations Research and Financial Engineering at Princeton University with minors in Computer Science, Cognitive Science, Linguistics, and Statistics & Machine Learning.
Hyewon Jeong
Hyewon Jeong is a Ph.D. student in EECS at MIT. Her primary research focus has been on applying machine learning models to solve real-world clinical problems, specifically tasks from time-series EHR data, signal data to multi-modal data. She is also interested in solving robustness, fairness, and causal inference applied to clinical and biomedical problems. Hyewon received B.S. in biological sciences and M.S. in Computer Science from Korea Advanced Institute of Science and Technology, M.D. in Yonsei University.