Improving the Fairness of Chest X-ray Classifiers

Publication
Conference on Health, Inference, and Learning
Haoran Zhang
Haoran Zhang

Haoran is a first-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.

Natalie Dullerud
Natalie Dullerud

Natalie Dullerud is a second-year M.S. student at University of Toronto, co-supervised by Dr. Marzyeh Ghassemi and Dr. Nicolas Papernot. Her research broadly focuses on various facets of fair and equitable machine learning; intersections between conceptualizations of privacy and machine learning; and applications in medical and biological contexts. Previously, she completed her B.S. in Mathematics at University of Southern California.

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