Machine Learning in Public Health: A 3-Day Intensive Workshop
July 8–10, 2026 | 9:00 AM – 5:00 PM
The Levy Library, Annenberg Building, Room 11-46
Icahn School of Medicine at Mount Sinai
Enter at 1468 Madison Avenue
Data is everywhere—but meaningful insight is rare. Machine learning (ML) is rapidly becoming an essential tool in public health research, from predicting disease outbreaks to analyzing environmental health risks. This intensive three-day workshop is designed to help researchers and health professionals develop practical ML skills for real-world public health applications.
Led by Vishal Midya, PhD, the workshop combines hands-on coding in R and R Studio with the statistical foundations behind machine learning methods. Participants will explore regression and classification models, decision trees, random forests, supervised learning, and feature engineering using real-world datasets.
By the end of the workshop, participants will understand when and how to apply machine learning methods, interpret model performance, and begin developing independent ML-based research projects.
Participants should have a working knowledge of R/R Studio, a basic understanding of epidemiology and biostatistics, and a laptop with R and R Studio pre-installed.
