Info

    • MD ( Medicine), Universidad Autónoma de Madrid, 1995

    • MPH (Public Health), Harvard School of Public Health, 1995

    • ScM (Biostatistics), Harvard School of Public Health, 1999

    • DrPH (Epidemiology), Harvard School of Public Health, 1999

  • Current

    • Professor, Harvard T.H Chan School of Public Health

    • Director, CAUSALab

    • Member of the Faculty, Harvard-MIT Division of Heath Sciences and Technology

    • Associate Member, Broad Institute

    • Principal Researcher, Karolinska Institutet

    Visiting faculty appointments

    • Visiting Professor (Statistics), Columbia University, 2013

    • Visiting Faculty (Epidemiology), Johns Hopkins Bloomberg School Public Health, 2015–19

    • Gästprofessor (Epidemiology), Karolinska Institutet, 2017–22

    • Adjunct Professor (Epidemiology), City University of New York, 2020

  • Current

    • Associate Editor (Methods), Annals of Internal Medicine, 2022–

    Past

    • Associate Editor, American Journal of Epidemiology,2005–19

    • Associate Editor, Biometrics, 2006–08

    • Editor, Epidemiology, 2007–20 (member of Editorial board, 2006–07)

    • Guest Editor, Statistical Methods in Medical Research, 2009–11

    • Editorial Board member, Journal of Causal Inference, 2011–20

    • Associate Editor, Journal of the American Statistical Association – Applications and Case Studies, 2012–17

  • Current

    • Member, Scientific Advisory Board, ADIA Lab, 2022-

    • Senior Scientific Advisor. Adigens Health 2025-

    • Member, Cancer Data Sciences, Dana-Farber/Harvard Cancer Center, 2015-

    • Data Analytics Collaborator, VA Boston Healthcare System, U.S. Department of Veterans Affairs, 2019-

    Past

    • Special Government Employee, U.S. Food and Drug Administration, 2014–18

    • Data Science Adviser, ProPublica, 2017–24

    • Member, Scientific Advisory Board, National French Health Data Hub, 2021-24

    • Fellow, la Caixa Foundation, 1995–97

    • Fellow, American Association for the Advancement of Science (AAAS), 2012

    • Highly Cited Researcher, Clarivate, 2015-

    • MERIT Award, National Institute of Allergy and Infectious Diseases, US NIH, 2018

    • Fellow, American Statistical Association, 2019

    • Alumni Award, Universidad Autónoma de Madrid, 2022

    • Rousseeuw Prize for Statistics, King Baudouin Foundation, Belgium, 2022

    • Lowell Reed Award, Applied Public Health Statistics Section, American Public Health Association, 2023

    Awards to research articles

    • Runner-up to Best Research Report, Health Research Training Program, New York City Department of Health, 1994

    • Kenneth Rothman Epidemiology Prize, Epidemiology journal, 2005 (co-author, 2021)

    • Article of the Year, American Journal of Epidemiology, top 10 article selected by the Editors and the Society for Epidemiologic Research, last author, 2014, 2015, 2016, 2021

    • Award for Outstanding Research Article in Biosurveillance, Category: Impact on the field, 2nd prize (last author), International Society for Disease Surveillance, 2016

    • Best article in Epidemiology, co-author of a top 4 article selected by the Spanish Society of Epidemiology, 2021

    • Influential Paper selected for the American Journal of Epidemiology Centennial, co-author of 2 of 4 selected influential articles published in the first 100 years of the American Journal of Epidemiology, 2021

    Awards for teaching and mentoring

    • Excellence in Teaching Citation, Harvard School of Public Health, 2005

    • Mentoring Award, Harvard School of Public Health, 2011

    • Outstanding Postdoctoral Mentor Award, Harvard T.H. Chan School of Public Health, 2019

Brief bio for formal introductions (use 1, 2, or 3 paragraphs)

Miguel Hernán is the Director of CAUSALab, the Kolokotrones Professor of Biostatistics and Epidemiology at the Harvard T.H. Chan School of Public Health, and faculty at the Harvard-MIT Division of Health Sciences and Technology. 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 contributed to shape health research methodology worldwide.

Miguel teaches causal inference methods to generate and analyze data for health policy and clinical decision making. At Harvard, he has mentored dozens of trainees. His free online course Causal Diagrams and book Causal Inference: What If, co-authored with James Robins, are widely used for the training of researchers.

Miguel 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 elected Fellow of the American Association for the Advancement of Science and the American Statistical Association, member of the Advisory Board of ADIA Lab, and Associate Editor of Annals of Internal Medicine. He was Special Government Employee of the U.S. Food and Drug Administration, Editor of Epidemiology, and Associate Editor of Biometrics, American Journal of Epidemiology, and Journal of the American Statistical Association. Miguel is a Co-Founder of Adigens Health.