Emily Alsentzer

Bio

Dr. Emily Alsentzer is an Assistant Professor in Biomedical Data Science and, by courtesy, Computer Science at Stanford University. Her research leverages machine learning (ML) and natural language processing (NLP) to augment clinical decision-making and broaden access to high quality healthcare. She focuses on integrating medical expertise into ML models to ensure responsible deployment in clinical workflows. Dr. Alsentzer completed a postdoctoral fellowship at Brigham and Women’s Hospital where she worked to deploy ML models within the Mass General Brigham healthcare system. She received 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).

Academic Appointments

• Assistant Professor, Department of Biomedical Data Science
• Assistant Professor (By courtesy), Computer Science

Boards, Advisory Committees, Professional Organizations

• Treasurer and Board Member, Association for Health Learning and Inference (https://ahli.cc/) (2021 - Present)

Professional Education

• Postdoctoral Fellow, Brigham and Women's Hospital
• PhD, Massachusetts Institute of Technology and Harvard Medical School, Health Sciences and Technology (HST) Program
• MS, Stanford University, Biomedical Informatics
• BS, Stanford University, Computer Science