Ziad Obermeyer is a physician and researcher who works at the intersection of machine learning and health. His research seeks to understand and improve decision making in public policy and clinical medicine, and drive innovations in health research. His work has been published in Science, The New England Journal of Medicine, JAMA, The BMJ, and Health Affairs. He is the recipient of an Early Independence Award from the Office of the Director of the National Institutes of Health, and the Young Investigator Award from the Society for Academic Emergency Medicine. His research is supported by the National Institutes of Health, the Robert Wood Johnson, the World Bank Group, and the Laura and John Arnold Foundation.
Dr. Obermeyer holds a BA (magna cum laude) from Harvard and an MPhil from Cambridge, where he was a Frank Knox fellow in the history and philosophy of science. He worked as a consultant to pharmaceutical and global health clients at McKinsey & Co. in New Jersey, Geneva, and Tokyo before returning to Harvard for his MD (magna cum laude). While a medical student, he worked as a full-time research scientist at the Institute for Health Metrics and Evaluation at the University of Washington, supported by the Bill & Melinda Gates Foundation. He completed his clinical residency in emergency medicine at the Brigham & Women's, Massachusetts General, and Boston Children’s Hospitals.