Department of Public Health

Machine Learning
in Public Health:
A 3-day intensive workshop

July 8, 9 & 10, 2026
TIME: 9:00 am – 5:00 pm
Location: The Levy Library, Annenberg Building, Room 11-46
Icahn School of Medicine at Mount Sinai
Enter at: 1468 Madison Avenue

REGISTER TODAY!

Data is Everywhere. Insight is Rare.

From predicting disease outbreaks to identifying patterns in environmental exposures, Machine Learning (ML) is no longer a "future technology"—it is an essential tool for the modern health researcher. This workshop bridges the gap between raw data and actionable public health solutions.

Why this workshop?

The Power of Prediction: Move beyond traditional statistics to build models that forecast outcomes.
Competitive Advantage: Gain the technical literacy required for high-impact publishing and modern research grants.
Transdisciplinary Application: Learn use cases ranging from disease diagnosis to climate-related health risks.

Learn by Doing. Leave with Results.

Led by Vishal Midya, PhD, this is a hands-on technical workshop. We bypass the "black box" of AI, teaching you the statistical foundations and the practical coding skills needed to conduct independent research.

You should have some proficiency in R and R Studio.

Technical Requirements: While we focus on making ML accessible, this is a "keyboard-on" workshop. Participants should have:
- Software Proficiency: A working knowledge of R and R Studio.
- Foundational Knowledge: A basic understanding of epidemiology and biostatistics.
- Equipment: A laptop with R and R Studio pre-installed (setup guide provided upon registration).

Curriculum Highlights

Regression & Classification: The foundations of predictive modeling.
Tree-Based Methods: Master Random Forests and decision trees.
Supervised Learning: Discover hidden clusters in population health data.
Feature Engineering: Learn to prepare "messy" real-world data for high-performance models.

Learning Objectives

By the end of this workshop, participants should be able to:

Build basic machine-learning models to solve public health problems.
Have an advanced understanding of machine-learning methods, specifically when to use one and when not to use one.
Understand the statistical underpinning of the models and how they can be modeled to address a public health problem.
Have the knowledge and skill sets to develop and conduct their machine learning research projects independently.

Mount Sinai Employee/Staff*

$1,000/pp (3-day total) Click below to register and submit payment. *Possible funding support opportunity: Potential & limited CTSA funding support may be available for eligible faculty and post-docs (not on a T1, T32, etc. grant). This requires a separate statement. Eligibility and approval will be determined by the Dean and Chair for the Department of Public Health. Apply by June 26 (details on registration form).

Non-Mount Sinai Employee/Staff

$1,200/pp (3-day total) Click below to register and submit payment.

Current Mount Sinai Student*

Special discounted rate: $250/pp. Click below to register and submit payment.
*Potential CTSA funding for students may be available. Approval by the Dean and Chair for the Department of Public Health. Apply by June 26 (details on registration form)