I talk a lot about data and causal inference.
That is a very broad topic. In fact, you can probably find a “data and causal inference” angle to almost everything in this world. Below you can watch a sample of recent talks I gave—on causal “AI”, coronavirus treatments, and the use of observational data—and an interview on causal knowledge as a prerequisite for confounding adjustment. If you are interested in watching applications of causal inference methods to health challenges, check out CAUSALab’s YouTube Channel.
If you prefer live events, in 2025 I plan to speak here:
February 12
Bohigian Lectureship in Biomedical Informatics
Washington University School of Medicine
Saint Louis, MO
March 27
International Workshop on HIV
and Hepatitis Observational Databases
Toledo, Spain
May 7
Workshop on Real-World Evidence for GLP-1-Based Therapies
National Institute of Diabetes Digestive and Kidney Diseases
Bethesda, MD
April 14
Melvin L. Samuels Lectureship
MD Anderson Cancer Center
Houston, TX
May 15
Session on Frontiers in Causal Inference
American Causal Inference Conference
Detroit, MI
June 5
Real World Evidence Summit
Sanofi
Paris, France
By invitation only
More coming soon
Stay tuned
If you prefer podcasts, here you can hear my views on causal inference and related issues.
(starts with a brief intro in Portuguese)