Marzyeh completed her PhD at MIT where her research focused on machine learning in healthcare, exploring how to predict immediate and long-term patient needs to inform decisions in the intensive care unit and ambulatory care. Her current research interests include clinical risk prediction with semi-supervised learning, optimal treatment discovery using expert demonstrations, and non-invasive patient phenotyping for behavioral conditions. Prior to MIT, she received a B.S. degree in computer science and electrical engineering at New Mexico State University as a Goldwater Scholar and Master’s degree in biomedical engineering from Oxford University as a Marshall Scholar. Marzyeh is on the Board of Women in Machine Learning (WiML), and co-organized both the NIPS 2016/2017 Workshop on Machine Learning for Health and MIT’s first Hacking Discrimination event.