Biography
Dr. Kim Phuc Tran
Dr. Kim Phuc Tran
the ENSAIT and the GEMTEX laboratory, University of Lille, France
Title: Machine Learning for Explainable Anomaly Detection in IoT systems: Methods, Applications, and Challenges
Abstract: 
The recent development of advanced technologies such as Smart Sensor Networks, the Internet of Things (IoT), and Artificial Intelligence (AI) drive continuous improvement, knowledge transfer, and data-driven decision-making in many fields. The problem of Anomaly Detection (AD) based decision-making support for the Industry 4.0 context is a major concern in a large number of studies. Anomaly Detection is a set of major techniques with an aim to detect rare events or observations that deviate from normal behavior. Applications of AD include intrusion detection in a computer network, spotting potential risk or medical problems in health data, and predictive maintenance. In this talk, I will present an overview of Anomaly Detection and the applications such as cybersecurity in IoT systems, production monitoring, predictive maintenance. I will present an overview of Explainable Anomaly Detection and the applications such as cybersecurity in IoT systems, production monitoring, predictive maintenance. I also discuss what challenges the current anomaly detection methods can address and envision this area from multiple different perspectives.
Biography: 
Kim Phuc Tran is currently an Associate Professor of Artificial Intelligence and Data Science at the ENSAIT and the GEMTEX laboratory, University of Lille, France. He obtained a Ph.D. in Automation and Applied Informatics at the Université de Nantes, France. His research works deal with Real-time Anomaly Detection with Machine Learning, Decision Support Systems with Artificial Intelligence, and Enabling Smart Manufacturing with Federated Learning. He has published more than 60 papers in SCIE peer-reviewed international journals and proceedings of international conferences. He edited 3 books with Springer Nature and CRC Press,Taylor & Francis Group. He is the Topic Editor and Guest Editor for Sensors journal. He has supervised 8 Ph.D. students and 2 Postdocs. In addition, as the project coordinator (PI), he is conducting 1 regional research project about Healthcare Systems with Federated Learning. He has been or is involved (co-PI or member) in 5 regional research 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 during the last 4 years.