Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing

Publication
arXiv preprint arXiv:2108.12510
Sindhu C. M. Gowda
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 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.

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