Ernest K. Kwegyir-Afful, PhD

Dr. Kwegyir-Afful is the Branch Chief of the Hazard Assessment and Analytics Branch within the FDA's Human Foods Program, where he has spent over a decade pioneering the use of artificial intelligence and advanced analytics to modernize food safety regulation in the federal government.

Ernest is the principal architect of WILEE (Warp Intelligent Learning Engine), the Human Foods Program's first comprehensive AI-powered surveillance system for food chemicals. WILEE integrates large and diverse data sources to perform signal detection, knowledge discovery, and horizon scanning across food additives, food contact substances, color additives, dietary supplements, and chemical contaminants, delivering faster, data-driven insights that strengthen the agency's ability to protect public health across both post-market surveillance and premarket analysis functions.

Ernest has been a central figure in shaping FDA's broader AI strategy. He has led CFSAN's AI interest group, served on the Executive Committee of FDA's agency-wide AI/ML Workgroup, and contributed to the New Era of Smarter Food Safety initiative as lead of the Predictive Analytics subgroup for Artificial Intelligence and Machine Learning. His earlier work designing CFSAN's "Emerging Chemical Hazard Intelligence Platform" was featured in KM World and the Harvard Business Review.

Ernest has also advised senior government officials from the Netherlands and Sweden on deploying AI within regulatory frameworks and was an invited panelist for the Harvard Business Review Executive Dinner Series on implementing AI in government and industry.

Ernest holds a PhD in Neuroscience from the University of Maryland School of Medicine, a Certificate in Data Science from Georgetown University, and a BSc (Hons) in Biochemistry and Psychology from the University of Ghana.

Dr. Yu Wang

Dr. Wang is a Health Informaticist at the U.S. Food and Drug Administration (FDA), where he develops bioinformatic and AI tools to study foodborne pathogens and support regulatory science. His current research includes applying transformer-based models to encode pathogen genomes and characterize their virulence, as well as developing LLM-powered AI agents to streamline the processing of consumer complaints on food and dietary supplements. He holds a Ph.D. in Biomedical Engineering from Marquette University and completed postdoctoral training in Bioinformatics and Systems Biology at the University of California, San Diego (UCSD).

Dr. Craig Schlenoff

Dr. Schlenoff currently serves as the Chief of the AI Research, Measurement, and Standards Division and the Senior Advisor for AI in the Information Technology Laboratory (ITL) in the National Institute of Standards and Technology (NIST). In this role, he advises the ITL Director and other NIST senior management on trends in AI and how NIST can best position itself to enable U.S. industry to lead in AI innovation. Prior to this, Dr. Schlenoff served as the NIST Acting Deputy Associate Director of Laboratory Programs (ADLP), where he advised the ADLP, provided operational guidance for NIST’s scientific and technical laboratory programs across six laboratories, led program and budget development, and coordinated interagency and outreach activities, accelerating U.S. innovation.

Prior to this, Dr. Schlenoff served as the Director of the Office of Science and Technology Policy’s (OSTP) Networking and Information Technology Research and Development (NITRD) National Coordination Office. In this role, he coordinated $11B of Federal Government IT R&D to identify, develop, and transition into use the secure IT, high-performance computing, networking, and software capabilities needed by the Nation, and fostered public-private partnerships that provide world-leading IT capabilities. He also served as the co-chair of the NITRD AI R&D Interagency Working Group, where he led the development of the 2023 AI R&D Strategic Plan Update.

Dr. Schlenoff received his bachelor’s degree in mechanical engineering at the University of Maryland College Park, his master’s degree in mechanical engineering from Rensselaer Polytechnic Institute, and his PhD in computer science from the University of Burgundy in Dijon, France.

Dr. Seneca Fitch

Dr. Fitch is a Managing Scientist and Director of ToxStrategies’ Health Sciences Practice, specializing in systematic evaluations of substances linked to consumer products, food additives, pharmaceuticals, and industrial chemicals. As an expert information specialist and evidence analyst, she supports the entire systematic review process, from problem formulation and protocol development to data extraction, critical appraisal, and evidence synthesis. Her current research focuses on automating systematic reviews in environmental and health-related risk assessments, integrating artificial intelligence and machine learning to optimize literature prioritization, evidence mapping, and systematic reviews. As a practitioner, Ms. Fitch has extensive hands-on experience with leveraging informatics platforms and custom AI-facilitated approaches to answer specific research questions. She is an active participant in the Evidence- Based Toxicology Collaboration, serving on its scientific advisory council and as Chair of the Research Methods Working Group. Ms. Fitch has co-authored 20 peer-reviewed publications and 2 book chapters, contributing to advancements in evidence-based toxicology and modern approaches to evidence synthesis.

Dr. Amarda Shehu

Dr. Shehu is a Professor of Computer Science, Associate Dean for Research, and Vice President and Chief AI Officer at George Mason University. In these roles, she leads Mason’s institution- wide AI strategy spanning research, education, workforce development, and external partnerships. She previously directed the Institute for Digital Innovation and has launched multiple transdisciplinary centers to accelerate cross-campus collaboration and translation. Shehu is also the primary architect of Mason’s AI education and literacy pipeline, including the university’s new M.S. in Artificial Intelligence degree and the general-education “AI for All” course. She chairs the university’s AI-in-Government Council, convening academia, industry, and public agencies to advance responsible, mission-driven AI adoption. Her national service includes prior work as an NSF Program Director in the CISE Directorate (2019–2022), and she continues to help shape AI, biosecurity, and innovation agendas across academia, government, and industry. An active AI researcher, Shehu has published over 200 papers with students and collaborators, sustaining a long-running research program at the intersection of AI and molecular biology that pioneers probabilistic, machine learning, and generative methods for protein science, genomics, and molecular design. Her contributions have been recognized through multiple awards for research, education, mentorship, and service, and by professional honors including election as a 2022 Fellow of the American Institute for Medical and Biological Engineering, IEEE Senior Member status, and membership in the Virginia Academy of Sciences, Engineering, and Medicine.

Steven M. Musser, PhD

Dr. Musser is currently the Associate Commissioner for Human Foods Research. In this role, he oversees an extensive research portfolio supporting priority human food programs including dietary supplements, microbiological food safety, and the safety assessments for food chemicals and contaminants. He’s published more than 100 articles in the peer reviewed scientific literature and regularly speaks on research topics at national and international scientific meetings.

Dr. Musser received his Ph.D. in Medicinal Chemistry from the University of Maryland in 1989. He then completed a post-doctoral research fellowship at the National Institutes of Health, National Cancer Institute. Following his post-doctoral training he started his career at FDA in 1991 as a research chemist.

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