My teaching explores the conditions required for causal inference and the methods (study design, data analysis) to make causal inferences when those conditions are met. Because I am an epidemiologist, the subject-matter of my courses is that of medicine and public health, and my target audience is researchers and clinicians who need to evaluate or generate evidence to support decision-making. My aim is to help them develop critical thinking, problem-solving skills, and the ability to articulate sound arguments.

At Harvard I lead core methods courses in several graduate programs. I teach clinical epidemiology at the Harvard-MIT Division of Health Sciences and Technology, and causal inference methodology at the Harvard T.H. Chan School of Public Health. I used to teach clinical data science at the Harvard Medical School and now teach in several programs of the Harvard Medical School Office of Global Education.

If you want to come to study at Harvard, my colleagues at the CAUSALab and I offer short courses in June in Boston.

Through HarvardX and edX, I offer the online course Causal Diagrams: Draw Your assumptions Before Your Conclusions. This course is free and accessible to anyone with an internet connection. The Assessments for the course are available here and the answers (don’t cheat, please) here. If you are interested in how a massive online course is made, Harvard Magazine published a short piece about our course.

Outside Harvard, I often teach short courses. This is my 2022 schedule: