Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing
Sindhu C. M. Gowda
I’m a graduate student at the University of Toronto advised by Prof. Marzyeh Ghassemi. I am broadly interested in causal inference and machine learning, specifically in their application to healthcare. I graduated from NIT Rourkela, India in 2017 with an integrated B.Tech-M.Tech degree in Electronics and Communication Eng. I am currently working as a part-time intern at Microsoft Research Montreal. I’d visited the University of Toronto in the summer of 2016 as a MITACS Globalink research intern.
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.