Ahmed Samet
Biography
Ahmed Samet is an associate professor with Habilitation (HDR) at INSA Strasbourg, France, and a member of the Data and Knowledge Science team at the ICube Laboratory (CNRS). His research focuses on artificial intelligence, machine learning, data mining, and their industrial applications in the context of Industry X.0. Over the past years, he has developed expertise in intelligent energy systems and AI-driven battery analytics, particularly for lithium-ion battery monitoring, predictive maintenance, and remaining useful life estimation. He has participated in several national and European research projects related to energy management, industrial AI, and smart systems. Ahmed Samet currently coordinates collaborative research activities involving both academia and industry, including partnerships with major actors in the energy sector such as EDF and EIFFAGE Energy. He is also an elected board member and secretary of the French Association for Artificial Intelligence (AFIA), the French branch of EurAI, and actively contributes to international conferences and scientific events in artificial intelligence and intelligent systems.
Title
Artificial Intelligence for Smart Battery Systems: From Data to Predictive Energy Management
Abstract
This presentation explores the role of artificial intelligence in the development of smart battery systems and next-generation energy storage solutions. The talk highlights how machine learning and data-driven approaches can be used throughout the battery lifecycle to improve performance, reliability, safety, and operational efficiency. Several AI-based methodologies will be presented, including battery state estimation, remaining useful life (RUL) prediction, anomaly detection, and predictive maintenance for lithium-ion batteries. The presentation also discusses the use of neural networks and intelligent data analytics for optimizing charging strategies, energy management, and battery system monitoring under real operating conditions.
Through industrial and research-oriented case studies, the talk illustrates how artificial intelligence is becoming a key enabler for intelligent battery management systems and sustainable energy infrastructures in the context of Industry X.0.