UMD Researchers Receive USDA Funding to Use Big Data Analytics and Machine Learning to Integrate Microbial Genomics with Food Safety Risk Assessment

The University of Maryland (UMD) recently received a grant from the United States Department of Agriculture National Institute of Food and Agriculture (USDA-NIFA) to develop a next-generation food safety risk assessment model by combining emerging techniques in both food safety and machine learning. Alongside the expertise of co-investigators Jianghong Meng, director of the UMD Joint Institute for Food Safety and Applied Nutrition (JIFSAN) and the Center for Food Safety and Security Systems (CFS3), Hector Corrada Bravo, associate professor in Computer Science at UMD, and Marc Allard as a collaborator from the U.S. Food and Drug Administration (FDA), Pradhan and his team are poised to lead the way in combining these tools to develop a next-generation quantitative microbial risk assessment (QMRA).

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