Dr. Emily Alsentzer is an Assistant Professor in Biomedical Data Science and, by courtesy, Computer Science at Stanford University. Her research develops trustworthy machine learning and natural language processing methods for healthcare, with a focus on settings with limited annotated data. Previously, Dr. Alsentzer was a postdoctoral fellow at Brigham and Women’s Hospital where she worked to deploy ML models within the Mass General Brigham healthcare system. She earned her PhD from the Health Sciences and Technology program at MIT and Harvard Medical School and holds degrees in computer science (BS) and biomedical informatics (MS) from Stanford University. She has served as General Chair for the Machine Learning for Health Symposium and founding organizer for SAIL and the Conference on Health, Inference, and Learning (CHIL).