I talk a lot about data and causal inference.
That is a remarkably broad topic. In fact, a “data and causal inference” angle can be applied to almost anything. Below is a selection of my recent talks as well as an interview on causal knowledge as a prerequisite for confounding adjustment. To explore more applications of causal inference methods in health research, check out CAUSALab’s YouTube Channel.
If you prefer live events, this academic year I plan to speak here:
August 1
Association of Clinical and Translational Statisticians
ACTStat Annual Meeting
Boston, MA
September 21
Joint Initiative for Causal Inference
University of Copenhagen
Copenhagen, Denmark
By invitation only
October 27
Trustworthy AI and Causal Learning
ADIA Lab Symposium
Abu Dhabi, UAE
August 25
Pontificia Universidad Javeriana
Departamento de Epidemiología Clínica
Bogotá, Colombia
December 15
Taiwan Causal Inference Symposium
Institute of Statistical Science
Taipei, Taiwan
Stay tuned
For more talks in the academic year 2026/27
August 31
International Society for Pharmacoepidemiology
Allianz Milan Convention Center
Milan, Italy
If you prefer podcasts, here you can hear my views on causal inference and related issues.
(starts with a brief intro in Portuguese)