Assistant Professor Jian Li of Data Science from the Department of Applied Mathematics and Statistics and the Department of Computer Science has been awarded a prestigious $1.2 million R01 grant from the National Institutes of Health to develop artificial intelligence systems that optimize how healthcare resources reach patients with diabetes, cardiovascular disease, and maternal health challenges.
The four-year grant, funded through the competitive NSF/NIH Smart and Connected Health program, positions Stony Brook as a leader in AI-driven healthcare innovation. Li serves as a Multiple Principal Investigator alongside Kai Wang of Georgia Institute of Technology, leading a collaboration that includes researchers from Harvard Medical School and Massachusetts General Hospital.
"Healthcare workers face an enormous challenge: how do you allocate limited resources to help the most people?" said Li, who is also a core faculty member of Stony Brook's AI Innovation Institute. "Our goal is to develop intelligent systems that can learn, adapt, and make fairer decisions about who receives interventions and when."
The project addresses a critical gap in public health delivery. Despite effective interventions for chronic diseases, limited healthcare budgets force difficult decisions about resource allocation. Li's team is pioneering advanced machine learning techniques called Restless Multi-Armed Bandits that make sequential decisions under uncertainty while accounting for patient diversity and social determinants of health.
The research will leverage major health datasets, including electronic health records from MIMIC-III, MIMIC-IV, the NIH All of Us Research Program, and Mass General Brigham Biobank. The team will also incorporate data from intervention trials such as REAL HEALTH-Diabetes, Look AHEAD, and the Diabetes Prevention Program to ensure real-world applicability.
"What makes this project particularly innovative is how we're accounting for the social determinants of health," explained Li. "We're developing models that consider patients' social networks, socioeconomic factors, and the constraints faced by decentralized healthcare providers."
Li brings substantial expertise to this endeavor as a recipient of the NSF CAREER Award in 2024 and the NSF CISE CRII Award in 2021. His research has earned multiple accolades, including the ACM/IEEE SC'24 Best Student Paper Finalist, and has been supported by NSF, ARO, NIH, and DOE.
Working with Georgia Tech's Kai Wang, who has deployed similar algorithms for maternal health programs in India, Georgia Tech's B. Aditya Prakash, an expert in computational epidemiology, and Harvard/MGH's Sara Cromer, a physician-scientist specializing in diabetes care, the team will develop scalable AI frameworks that translate computational innovations into clinical practice.
The project runs from September 2025 through June 2029, with Stony Brook receiving approximately $300,000 of the total award.