Miguel Hernán
Miguel Hernán, MD, DrPH, is the Kolokotrones Professor of Biostatistics and Epidemiology at the Harvard T.H. Chan School of Public Health.
Professor Hernán uses health data and causal inference methods to learn what works. As Director of CAUSALab at Harvard, he and his collaborators repurpose real world data into evidence for the prevention and treatment of infectious diseases, cancer, cardiovascular disease, and mental illness. This work has helped shape health policy and research methodology worldwide.
Hernán is co-director of the Laboratory for Early Psychosis (LEAP) Center, principal investigator of the HIV-CAUSAL Collaboration, and co-director of the VA-CAUSAL Methods Core, an initiative of the U.S. Veterans Health Administration to integrate high-quality data and explicitly causal methodologies in a nationwide health learning system. His free online course Causal Diagrams and his book Causal Inference: What If, co-authored with James Robins, are widely used for the training of researchers. According to Google Scholar, his numerous publications have been cited more than 110,000 times.
Hernán has received several awards, including the Rousseeuw Prize for Statistics, the Rothman Epidemiology Prize, and a MERIT award from the U.S. National Institutes of Health. He is a Fellow of the American Association for the Advancement of Science and the American Statistical Association. He is currently Associate Editor of the Annals of Internal Medicine and Editor Emeritus of Epidemiology.
You can visit his university webpage here.