PROVISIONAL PROGRAMME   THURSDAY 29 OCTOBER 2026 (AFTERNOON)   DAY 1 / Foundations of Artificial Intelligence: Understanding, Trust and Data   13:30 Registration   14:00 Opening remarks - ANSES   14:10 Opening Keynote - AI: What Are We Talking About? Concepts, Methods and Limitations     Prof. Dr Patrick Glauner, Full Professor of Artificial Intelligence, Deggendorf Institute of Technology, Germany     Questions 15:00 SESSION 1 / Validation, Explainability and Trust   Keynote - From Data to Evidence: Building Trust in AI-Enabled Scientific Workflows     Dr. Nina Jeliazkova, Ideaconsult Ltd, Burlgaria   Establishment of Readiness Criteria for AI-based tools for risk assessment: READYAI     Dr. Joyce de Paula Souza, Swiss Centre for Applied Human Toxicology, University of Basel Switzerland   Trusting AI Without Losing Control: A Modeller’s Perspective     Laurent Guillier, ANSES, Risk Assessment Department, France   Title to be confirmed – Link with the AI in Science Summit - How can AI help Europe understand interconnected One Health systems?     Gerald Barry, Deputy Director of the UCD One Health Centre, Ireland   From Food Industry Data to Scientific Evidence: Opportunities and Challenges     Fanny Tenenhaus-Aziza, CNIEL - National Inter-professional Centre for the Dairy Industry, France   16:30 Coffee break 17:30 SESSION 2 / From Data and Scientific Evidence to AI   Paper2Model Agents in RAKIP     Matthias Filter, Study Centre Supply Chain Modelling and Artificial Intelligence - BfR - German Federal Institute for Risk Assessment, Germany   A Retrieval-Augmented Natural Language Interface for Data Description and Meta-Analysis in the Pathogens-in-Foods (PIF) Database     Ursula Gonzales-Barron, IPB - Polytechnic Institute of Bragança, Portugal   From Omics Data to Biological Insights: The Role of AI in Nanosafety     Andrea Haase, Unit Fibre & Nanotoxicology BfR - German Federal Institute for Risk Assessment, Germany   Automating Food Classification Using LLMs: Application to the European FoodEx2 Classification System     Thomas El Khilali, Methodology and Research Unit ANSES, France   18:00 Cocktail   FRIDAY 30 OCTOBER 2026 (FULL DAY)   DAY 2 / From Models to Decision-Making   8:30 Registration and welcome coffee   9:00 Welcome 9:15 SESSION 3 / AI for risk assessment   Keynote - AI for Risk Assessment: From Faster Analysis to Accountable Scientific Reasoning     Dr. Didier Verloo, Head of Knowledge, Innovation and Partnerships, EFSA - European Food Safety Authority, Italy   Implementation of AI-Based Support Systems in the Risk Assessment of Microorganisms     Ikbel Guidara, Federal Office of Consumer Protection and Food Safety, Germany   Artificial Intelligence in Food Safety     Dr. Floor van Meer, Senior researcher Data Science, Wageningen Food Safety Research, The Netherlands   AI in Regulatory Food and Feed Safety Assessment: Current Uses, Challenges and Priorities     Didier Verloo on behalf of ILMERAC, International Liaison Group on Methods for Risk Assessment of Chemicals in Food and Feed, EFSA, Italy   AI-Assisted Risk Assessment: Managing Complexity with Speed, Transparency and Consistenc     Moez Sanaa, IFORAC - International Food Risk Analysis Consortium, Paris   10:45 Coffee break 11:15 SESSION 4 / AI for Surveillance and Early Detection   PIFAlert: An Explainable, Evidence-Aware Recommender System for Foodborne Pathogen Surveillance     Vasco Cadavez, Animal Science Department - IPB - Polytechnic Institute of Braganza, Portugal   Toward Predictive Food Safety: Korea's Experience with AI-Enabled Surveillance, Early Detection, and Risk Assessment     Hyang Sook Chun, Department of Food Science and Technology, Chung-Ang University, South Korea   Forecasting Glycoalkaloid Contamination in Danish Potatoes using Machine Learning: A study of environmental effects on food safety     Armando Morin Martinez , Research Group for Chemical Risk Assessment and GMO, DTU – Danish Technical University, Denmark   Deep Learning for pathogen analysis     Alfred Ferrer Florensa, Research Group for Genomic Epidemiology DTU – Danish Technical University, Denmark   12:05 Lunch 13:30 SESSION 5 / Case Studies and Implementation   Leveraging Large Language Models to Capture Emerging Food Practices Relevant to Microbial Risk Assessment under Climate Change     Estelle Chaix, Food Risk Assessment Unit, ANSES, France   Consensus through design: How AI-based risk negotiations are transforming One Health     Dr. Alexandra Fetsch, Ludwig-Maximilians-Universität München, Germany   Mapping the Risk of West Nile Virus in Equines in Europe     Eric Morignat, Epidemiology and Support for Surveillance Unit, ANSES, France   A Machine Learning Framework for Food Source Attribution of Listeria monocytogenes     Isis Lorenzo, SPAAD, ANSES, France France   DirectPred – Same-day pathogen mitigation: Leveraging sequencing and AI for direct phenotypic prediction     Patrick Njage, Research Group for Genomic Epidemiology, DTU – Danish Technical University, Denmark   Danish (Q)SAR Database & Models and associated QSAR software     Eva Bay Wedebye and Nikolai Georgiev Nikolov, Research Group Chemical Risk Assessment and GMO DTU – Danish Technical University, Denmark 15:45 CLOSING ROUNDTABLE / AI in Risk Analysis: What is Realistic in the Next 5–10 Years?   16:15 Conclusions and closing remarks   Copyright © 2026 Ptolémée.