Marzyeh Ghassemi is an Assistant Professor at the University of Toronto in Computer Science and Medicine, affiliated with the Vector Institute. Previously, she was a Visiting Researcher with Alphabet's Verily and a post-doc with Dr. Peter Szolovits at MIT (CV).
Marzyeh's PhD research at MIT focused on creating and applying machine learning algorithms towards improved prediction and stratification of relevant human risks with clinical collaborations at Beth Israel Deaconess Medical Center and Massachusetts General Hospital, encompassing unsupervised learning, supervised learning, and structured prediction. Marzyeh’s work has been applied to estimating the physiological state of patients during critical illnesses, modeling the need for a clinical intervention, and diagnosing phonotraumatic voice disorders from wearable sensor data.
Her work has appeared in KDD, AAAI, IEEE TBME, MLHC, JAMIA, JMIR, JMLR and AMIA-CRI; she has also organized the 2014 NIPS Women in Machine Learning Workshop (WiML), the 2016/2017/2018 NIPS Workshop on Machine Learning for Health (ML4HC), and MIT's first Hacking Discrimination event. Prior to MIT, Marzyeh received an MSc. degree in biomedical engineering from Oxford University as a Marshall Scholar, and B.S. degrees in computer science and electrical engineering as a Goldwater Scholar at New Mexico State University.
This year she was honored to be named one of MIT Tech Review's 35 Innovators Under 35 in the Visionary category, a finalist for AMIA 2018 Doctoral Dissertation Award, and receive both a NSERC 2018 Discovery Grant, and MIT's 2018 Seth J. Teller Award for Excellence, Inclusion and Diversity. She also served as an Academic Guest Editor on the 2018 PLoS ONE call on Machine Learning in Health and Biomedicine, speaker at The Digital Doctor: Health Care in an Age of AI and Big Data IACS SYMPOSIUM, a panelist at AMIA 2018 Informatics Summit Panel on Deep Learning for Healthcare - Hype or the Real Thing?