Artificial Intelligence (AI) and especially Machine Learning (ML) are the driving energy behind industrial and technological transformation. With the transition from industry 4.0 to 5.0, smart manufacturing proves the efficiency in industry, where systems become increasingly complex, producing massive data, necessitating more demand for transparency, privacy, and performance. Federated Learning has demonstrated its effectiveness in various applications, however, there are still exist certain challenges that should be addressed. Thus, in this talk, a comprehensive perspective on federated learning-based anomaly detection is provided. The problems have posed concerns and should be taken into account when researching and deploying. Then, our perspectives about efficient and trustworthy federated learning-based explainable anomaly detection systems are demonstrated as an end-to-end unified framework. Finally, to provide a complete picture of future research direction, the quantum aspect is introduced in the subject of machine learning.

Kim Phuc Tran is currently a Senior Associate Professor (Maître de Conférences HDR, equivalent to a UK Reader) of Artificial Intelligence and Data Science at the ENSAIT and the GEMTEX laboratory, University of Lille, France. He received an Engineer's degree and a Master of Engineering degree in Automated Manufacturing. He obtained a Ph.D. in Automation and Applied Informatics at the University of Nantes, and an HDR (Doctor of Science or Dr. habil.) in Computer Science and Automation at the University of Lille, France. His research deals with Explainable Artificial Intelligence, Federated Learning, Reinforcement Learning, Cybersecurity, and Decision Support Systems with applications in industrial systems, such as production systems, industrial control systems, and healthcare systems. He is the Associate Editor, Editorial Board Member, and Guest Editor for several international journals such as IEEE Transactions on Intelligent Transportation Systems and Engineering Applications of Artificial Intelligence. He has been or is involved (co-PI or member) in several national and European projects. He is an expert and evaluator for the Research and Innovation program of the Government of the French Community, Belgium. He received the Award for Scientific Excellence (Prime d’Encadrement Doctoral et de Recherche) given by the Ministry of Higher Education, Research and Innovation, France for 4 years from 2021 to 2025 in recognition of his outstanding scientific achievements. From 2017 until now, he has been the Senior Scientific Advisor at Dong A University and the International Research Institute for Artificial Intelligence and Data Science (IAD), Danang, Vietnam where he has held the International Chair in Data Science and Explainable Artificial Intelligence.