LEMoN: Label Error Detection using Multimodal Neighbors
Haoran Zhang
Haoran is a fourth year PhD student in EECS at MIT. He is generally interested in building robust machine learning models that maintain their performance and fairness across out-of-distribution environments, as well as applying such models to the healthcare setting. Haoran previously received his M.Sc. at the University of Toronto under the co-supervision of Dr. Marzyeh Ghassemi and Dr. Quaid Morris, and his B.Eng. from McMaster University.
Aparna Balagopalan
Aparna Balagopalan is a fifth year PhD student in EECS at MIT. Her research broadly focuses on developing fair and robust models by re-evaluating and surfacing assumptions in machine learning-based measurements in socially-relevant contexts like healthcare. Prior to this, she received a Master’s degree from the University of Toronto and a BTech degree from IIT Guwahati. She currently holds an Amazon Doctoral Fellowship from MIT’s Science Hub.
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.