The University of Hawaiʻi at Mānoa received a $2 million award from the National Science Foundation to lead development of AI tools that detect environmental threats to food production systems before they escalate. The four-year project, which began September 1, arrives as public health officials investigate foodborne illness outbreaks tied to cyclospora - highlighting the need for faster, proactive detection methods in the food supply.
This is only the second time the university has received an NSF Established Program to Stimulate Competitive Research (EPSCoR) Track II Focused EPSCoR Collaboration award. The total project funding reaches $4 million, with the University of Nebraska-Lincoln joining as a partner institution.
How the technology works
The project combines artificial intelligence with environmental sampling, advanced genetic analysis, and high-resolution chemical analysis. Researchers will build AI models capable of interpreting complex biological and chemical data, including metagenomics - the study of genetic material collected from environmental samples - and high-resolution mass spectrometry, which identifies chemical compounds.
The team will test these technologies in aquaculture and beef cattle production systems. The goal is to improve food safety, protect animal health, and increase the resilience of food production systems against microbial pathogens and chemical contaminants.
Cross-institutional research team
Principal investigator Tao Yan, director of the Water Resources Research Center and professor in the Department of Civil, Environmental and Construction Engineering, leads the effort. Researchers from across the UH system are involved, including the Water Resources Research Center, College of Engineering, UH Cancer Center, School of Ocean and Earth Science and Technology, and College of Tropical Agriculture and Human Resilience.
"Food production systems are increasingly challenged by microbial pathogens and chemical contaminants that can threaten animal health, food safety and economic sustainability," Yan said in a university release. "By combining environmental surveillance with [artificial intelligence], we aim to develop early-warning technologies that can identify emerging risks before they reach critical levels."
Yan added that the collaboration will strengthen Hawaiʻi's and Nebraska's research capacity while preparing the next generation of scientists and engineers to address complex challenges in food security.
Workforce development and outreach
Beyond the research, the project includes structured outreach to industry partners, regulators, and communities to encourage adoption of the new technologies. It also supports STEM education and workforce development by creating research opportunities for junior faculty members, graduate and undergraduate students, and K-12 participants.
Why this matters for science and research professionals
This project signals growing NSF investment in applied AI for environmental monitoring - a domain where research scientists increasingly need to bridge machine learning with domain-specific data types like metagenomics and mass spectrometry. The multi-institutional structure also creates funded opportunities for early-career researchers and students to gain hands-on experience with AI model development outside traditional tech hubs.
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