NIH funds cross-campus effort to train experts in AI and nutrition
Cornell has received a $1.7 million grant from the National Institutes of Health (NIH) to develop a program that combines precision nutrition with advanced data science and analytical methods, equipping students to address complex health challenges like nutrition disparities and diet-related chronic diseases.
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The Artificial Intelligence and Precision Nutrition Training Program (AIPrN) will bring together Cornell faculty members in nutrition, medicine, biomedical sciences, computer and information science and engineering. Faculty members from the United States Military Academy at West Point and the University of California, San Diego will provide additional support.
“The program is designed to train scientists equipped with expertise in artificial intelligence and machine learning to address complex biomedical challenges in nutrition and health using high dimensional data,” said Saurabh Mehta, the Janet and Gordon Lankton Professor in the Division of Nutritional Sciences (College of Human Ecology), and the principal investigator on the grant.
Malnutrition – which includes both undernutrition and obesity – is one of the leading contributors to poor health and premature death, Mehta said. But, he added, the solution is not as simple as just eating the right amount of the right food.
Researchers have found that the relationship between diet and disease is complicated, involving genetics, health status, microbiome, eating patterns, food environment and socioeconomic standing. Precision nutrition takes these factors into account to tailor dietary guidance at the individual level. Researchers hope the increased availability of complex data related to public health will help reduce malnutrition.
“Nutrition and related biomedical disciplines increasingly collect and rely on big and complex data,” said Deborah Estrin, the Robert V. Tishman ‘37 Professor and associate dean for impact at Cornell Tech and one of five other principal investigators working with Mehta. “The next generation of scientists needs to be trained in advanced data analytics and computational approaches to understand and analyze such data.”
“It is exciting to explore how artificial intelligence can enable new ways of approaching problems in nutrition, and at scales and levels of detail that go beyond what is tractable otherwise,” said Thorsten Joachims, professor and associate dean for research in the Cornell Ann S. Bowers College of Computing and Information Science and another principal investigator.
The other PIs are David Erickson, the Sibley College Professor of Mechanical Engineering (Cornell Engineering); Rulla Tamimi, chief of epidemiology in the Department of Population Health Sciences at Weill Cornell Medicine; Martin Wells, the Charles A. Alexander Professor of Statistical Sciences (ILR School and College of Agriculture and Life Sciences); and Diana Thomas, professor of mathematics at West Point.
AIPrN builds upon NIH’s investment in precision nutrition research at Cornell, which includes a research coordinating center for the NIH’s Nutrition for Precision Health study that is co-led the Division of Nutritional Sciences and the nonprofit research institute RTI International. It’s the first time that NIH has funded a training program focused on AI, a recognition of the potential of technology to transform public health.
The program will be based in the Center for Precision Nutrition and Health (CPNH) in the College of Human Ecology, where Mehta is lead, with positions for four doctoral students and one postdoctoral fellow each year.
“Malnutrition is one of the key challenges of our time,” Mehta said. “This program is an opportunity to use the lens of precision nutrition and bring different disciplines together to improve human health".
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