Dr. Davide La Torre, PHD, HDR, is a Full Professor of Applied Mathematics and Artificial Intelligence at SKEMA Business School, Université Côte d’Azur, Sophia Antipolis Campus, France. He has more than 25 years of academic experience, and he has held permanent and visiting university professor positions in Europe, Canada, Middle East, Central Asia, and Australia. He has also served as Associate Dean, Departmental Chair and Program Head at several universities. He holds the French and the Italian national qualification as Professeur des Universités/Professore Ordinario (Full Professor) in several areas including Applied Mathematics, Computer Science, and Economics. His research program could be classified under the general title of Artificial Intelligence Fundamentals, Imaging, and Modeling. Main research topics include: Artificial Intelligence, Machine Learning, Mathematical Economics, Mathematical Imaging, Mathematical Epidemiology, Mathematical Medicine, and Optimization and Control. Prof. Davide got his HDR (Habilitation à Diriger des Recherches) in Applied Mathematics from the Université Côte d’Azur, Nice, France (2021), a Doctorate in Computational Mathematics and Operations Research (2002) and a Laurea (combined BSc and MSc) in Mathematics (1997, 110/110 cum laude) both from the University of Milan, Milan, Italy. He has professional certificates in Analytics, Artificial Intelligence, and Machine Learning from the Massachusetts Institute of Technology, USA. He has authored/coauthored more than 240 publications in Scopus, most of them published in high IF journals ranging from Applied Mathematics to Artificial Intelligence, from Business to Economics, from Finance to Engineering.
Multicriteria Decision Making and Goal Programming in the Age of Artificial intelligence
In an era where decisions are increasingly complex and data-driven, multicriteria decision making (MCDM) and goal programming (GP) emerge as fundamental tools for evaluating multiple and conflicting criteria. This talk explores the intersection of MCDM and GP with artificial intelligence (AI) and machine learning (ML), focusing on how AI and ML can enhance traditional decision-making processes, provide deeper insights into data pattern, and facilitate more informed choices in different fields from healthcare to environmental management, from engineering to finance. We will also show how MCDM and GP can support critical tasks in AI, focusing on the case of federated and adversarial learning. Attendees will gain a comprehensive understanding of the synergies between MCDM/GP and AI/ML and how they can be applied to real-case scenarios.
Dr. Chan Yeob Yeun received the M.Sc. and Ph.D. degrees in information security from the Royal Holloway, University of London, in 1996 and 2000, respectively. He joined Toshiba TRL, Bristol, U.K. Then, he became a Vice President of LG Electronics, Mobile Handset R&D Center, Seoul, South Korea, in 2005. He was responsible for developing the Mobile TV technologies and its security. He left LG Electronics, in 2007. He was with KAIST, South Korea, from 2007 to 2008. He has been with Khalifa University Science and Technology, since 2008. He is currently researching in cyber security that includes the IoT/USN security, cyber physical system security, Cloud/Fog Security, and Cryptographic techniques, as an Associate Professor, with the Computer Science Department and a Cybersecurity Team Leader of the Center for Cyber-Physical Systems (C2PS). Also, he enjoys lecturing M.Sc. in cyber security and Ph.D. in engineering courses at Khalifa University. He has published a number of journal papers, conference papers, and ten book chapters. He holds ten international patent applications. He is also serving as several Editorial Board members of International Journals and steering committee members of International Conferences. Recently, he was listed as the top 2% cited scientists in the Standford list.
Emerging Logistics for Cyber Security via IoT Networks
Emerging supply chains need an extra layer of cyber security to ensure that an enemy cannot compromise or steal their assets. Nations and groups are increasingly using cyber warfare against Logistics. There is a need for a secure cryptographic protocol that can add a strong level of cyber security to each type of tag on different phases of the supply chain. Many countries have implemented IoT/RFID/NFC technology to deal with challenges of visibility and tracking of materials ranging from consumable logistics items to logistics operations using different kinds of an IoT/RFID/NFC tag attached to them. Many studies have been done on how to secure a commercial supply chain management, especially when it comes to RFID/NFC tags that are placed on various materials regardless of their type. Unfortunately, there is little research that has been done in the area of securing supply chain management. My talk is to address emerging logistics cyber security via IoT networks to secure the different stages by using IoT/RFID/NFC techniques.