Lectures and seminars Miguel Hernán: What does “learning from data” mean? A taxonomy of tasks for health data science
We are pleased to be joined by Miguel Hernán, Harvard University, who will give a talk entitled: What does “learning from data” mean? A taxonomy of tasks for health data science.
About the Speaker:
Miguel Hernán, MD, MPH, ScM, DrPH, is the Director of the CAUSALab, Kolokotrones Professor of Biostatistics and Epidemiology at the Harvard T.H. Chan School of Public Health, Boston, USA and Member of the Faculty at the Harvard–MIT Program in Health Sciences and Technology. He is a former Guest Professor at the Institute of Environmental Medicine (IMM) at Karolinska Institutet, and now Principal Reseacher at CAUSALab IMM, Karolinska Institutet.
His research is focused on methodology for causal inference, including comparative effectiveness of policy and clinical interventions. Hernán conducts research to learn what works to improve human health. Together with his collaborators from several countries, he designs analyses of healthcare databases, epidemiologic studies, and randomized trials.
He is a Highly Cited Researcher. His free edX course Causal Diagrams: Draw Your Assumptions Before Your Conclusions is widely used. His book Causal Inference: What If, co-authored with James Robins is also freely available online and widely used for the training of researchers. Hernán is one of the four laureates of the 2022 Rousseeuw Prize for Causal Inference with applications in Medicine and Public Health.
Faculty website: https://www.hsph.harvard.edu/miguel-hernan/
Host: Anita Berglund, IMM
Registration: https://survey.ki.se/Survey/33143 (latest December 13)