At NYU Langone’s Comprehensive Program on Obesity, we integrate population health, clinical medicine, and basic science to develop new study tools and methodologies that may transform our ability to prevent, treat, and manage this disease.

By including rich data resources from multiple clinical and basic science domains, our investigators are able to address long-standing questions from completely new perspectives using cutting-edge machine learning and other big data techniques. We can then translate key insights into real, evidence-based solutions that can be quickly and effectively adopted by clinicians.

This approach helps us answer novel questions that are influenced by many factors, such as the effect of environmental determinants and the microbiome, topics that are featured prominently in our population health and discovery research. Biosamples and clinical targets shape our clinical and discovery research. Clinical data and social determinants affect the direction of our clinical and population health research.

In addition to discovery research, we lead research studies to explore the efficacy of treatments for obesity, such as bariatric surgery, and to develop more powerful tools for predicting pediatric obesity.