An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare
Taylor Killian
Taylor is a fifth-year PhD student in the CS Department at the University of Toronto, affiliated with Vector Institute, MIT’s CSAIL and IMES. His research interests combine Reinforcement Learning, Causal Inference and Representation Learning in pursuit of developing clinical decision support tools that generalize beyond the environment they were trained in, robust to sources of uncertainty such as distribution shift or covariate mismatch.
Haoran Zhang
Haoran is a third 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.