AI Detection of Norovirus Outbreaks

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Last Updated: Apr 10, 2026, 09:53 AM

School of Computing Professor Receives $300,000 USDA-NIFA Award for AI-Driven Early Detection of Norovirus Outbreaks in Shellfish Aquaculture

CARBONDALE, Ill. — April 10, 2026

USDA NIFA Grant
DSFAS: AI-Driven Predictive Modeling for Early Detection of Norovirus Outbreaks in Oyster and Shellfish Aquaculture

Dr. Zhong Chen, faculty member in the School of Computing, has received a highly competitive and prestigious USDA-NIFA award for his research project titled “DSFAS: AI-Driven Predictive Modeling for Early Detection of Norovirus Outbreaks in Oyster and Shellfish Aquaculture.” Dr. Chen serves as the project’s Principal Investigator in collaboration with a faculty member from the School of Electrical, Computer, and Biomedical Engineering.

The award totals $300,000 and supports the project from February 2026 through January 2028 through the U.S. Department of Agriculture’s National Institute of Food and Agriculture (USDA-NIFA).

Norovirus is one of the most common causes of foodborne illness worldwide and poses a significant public health risk when it contaminates oysters and shellfish grown in fecally polluted coastal waters. Despite continued monitoring and statistical modeling efforts, reliably predicting outbreaks before they occur remains a major challenge.

Norovirus
Norovirus contamination in oysters and shellfish poses a persistent public health risk, creating an urgent need for early detection and predictive warning systems in aquaculture environments.

This project addresses that gap by developing an advanced AI-powered early detection and forecasting system capable of delivering timely warnings and actionable insights to aquaculture producers, public health officials, and food safety regulators.

The project will focus on enhancing early detection and warning systems by integrating multi-modal data and leveraging large language models (LLMs) to provide text-based explanations of prediction results. The research has the potential to improve food safety in aquaculture and protect exposed human populations.

 

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