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SUMMARY:Extreme food risk analytics (Horizon Europe)
DESCRIPTION:Tony Lindgren \n\n\n\nNBIS and SciLifeLab Data Centre arrange an open SciLifeLab AI Seminar Series aimed at knowledge-sharing about Artificial Intelligence and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min presentation and 15 min discussion. \n\n\n\nWhen: November 20\, 10:00-11:00 \n\n\n\nWhere:  Zoom http://meet.nbis.se/ainw \n\n\n\nSpeaker: Tony Lindgren \n\n\n\nSenior Lecturer\,. Head of the Systems Analysis and Security Unit\, Department of Computer and Systems Sciences (DSV)\, Stockholm University \n\n\n\nAbstract \n\n\n\nI will present an overview of the research project\, Extreme Food Risk Analytics (EFRA) and also more deeply present some of the contributions made by Stockholm University within this setting. \n\n\n\nThe aim of the project was to increase food safety for European citizens. The project acknowledges that there is a wide array of data sources holding crucial information about the food that we eat. The problem is that these sources are heterogeneous – and sometimes hidden. In the project we explored how data can be mined\, aggregated and analyzed using AI. Not taking full advantage of this wealth of public and private data comes at a great cost: Despite best efforts and modern techniques\, consumers world-wide still get sick from contaminated foodstuff and food companies suffer huge economic and legal penalties from product food recalls. \n\n\n\nEFRA’s core ambition was to overcome these boundaries by exploring novel\, experimental and promising approaches in extreme data mining\, aggregation\, and analytics technologies. By recognizing and collecting this wealth of heterogeneous data\, scattered throughout the internet\, and convert it into a “universal language” of high-quality risk food data\, EFRA will be able to train AI-models to proactively provide risk mitigation measures (based on predictive awareness of short- and long-term risks) with an explainable\, secure\, sensitive\, accurate\, trustworthy\, fair and green manner\, before occurrence of potential food safety hazard. \n\n\n\n \n\n\n\nAbout the speaker: The speaker is an associate professor at the Department of Computer and Systems Sciences (DSV)\, Stockholm University. In 2006 he received his Ph.D. degree in computer and system sciences. He has worked both in academia and industry since 2008\, he is the inventor of numerous patents and the author of numerous scientific articles. His research is aimed at exploring machine learning in general but has a special interest in using data-driven methods for predictive maintenance problems. During his time at Scania\, Dr. Lindgren worked on applying his research to solve practical problems such as the maintenance optimization of Scania heavy trucks. Since 2019\, Tony Lindgren has been the head of the Systems Analysis and Security Unit at DSV\, Stockholm University. \n\n\n\nTo stay updated\, you can join our email list by contacting ai-network@scilifelab.se. \n\n\n\n\nJoin Seminar
URL:https://www.scilifelab.se/event/extreme-food-risk-analytics-horizon-europe/
LOCATION:Online event via Zoom
CATEGORIES:Event
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