Marzyeh completed her PhD at MIT where her research focused on machine learning in health care, 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 and Master’s degree in biomedical engineering from Oxford University. Marzyeh is on the Board of Women in Machine Learning (WiML), and co-organized the NIPS 2016/2017 Workshop on Machine Learning for Health, and MIT’s first Hacking Discrimination event.