Calvin Slaughter is a Ph.D. candidate in the Snyder Lab housed within the Department of Food Science at Cornell University. His research is centered around using machine learning approaches to answer applied food safety questions ranging from predicting microbial responses to moisture ingress in low-moisture food facilities to using hygiene indicator data to identify patterns in sanitation performance. Through his involvement with Cornell Cooperative Extension, Calvin works to translate this research into practical tools and educational resources for food manufacturers. His Extension work has included developing and delivering workshops on the responsible use of generative artificial intelligence in food safety documentation, statistical process control tools for hygiene indicator monitoring, and developing custom large language models for food safety applications.