Jian Li Secures $1.2M NIH Grant to Revolutionize Healthcare Resource Allocation with AI
Jian Li
Jian Li

Jian Li, an assistant professor of data science in Department of Applied Mathematics and Statistics and Department of Computer Science, has been awarded a prestigious $1.2 million R01 grant from the National Institutes of Health (NIH) 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.​

Read the full story at the Computer Science website.

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Department of Computer Science