Keynote Speakers

Prof. Merouane Debbah, Khalifa University, Abu Dhabi, UAE

 Pioneering Intelligent Connectivity for the Future of Generative AI

Abstract: As telecommunications evolves into the backbone of global digital transformation, the integration of Generative AI stands at the forefront of this revolution. In this talk, we will explore how TelecomGPT redefines the way we approach intelligent connectivity. From enhancing customer service to optimizing network performance, Generative AI is bridging the gap between vast datasets and actionable insights. We will address in particular the broader implications of Generative AI in telecommunications, from transforming operational efficiency to enabling the 6G era of distributed, low-latency AI.

Bio: Mérouane Debbah is Professor at Khalifa University of Science and Technology in Abu Dhabi and founding Director of the KU 6G Research Center. He is a frequent keynote speaker at international events in the field of telecommunication and AI. His research has been lying at the interface of fundamental mathematics, algorithms, statistics, information and communication sciences with a special focus on random matrix theory and learning algorithms. In the Communication field, he has been at the heart of the development of small cells (4G), Massive MIMO (5G) and Large Intelligent Surfaces (6G) technologies. In the AI field, he is known for his work on Large Language Models, distributed AI systems for networks and semantic communications. He received multiple prestigious distinctions, prizes and best paper awards (more than 50 IEEE best paper awards) for his contributions to both fields and according to research.com is ranked as the best scientist in France in the field of Electronics and Electrical Engineering. He is an IEEE Fellow, a WWRF Fellow, a Eurasip Fellow, an AAIA Fellow, an Institut Louis Bachelier Fellow, an AIIA Fellow and a Membre émérite SEE. He is actually chair of the IEEE Large Generative AI Models in Telecom (GenAINet) Emerging Technology Initiative and a member of the Marconi Prize Selection Advisory Committee.

Prof. ABBAS-TURKI Abdeljalil, CIAD Laboratory: Knowledge and Distributed Artificial Intelligence, University of Technology - Belfort-Montbéliard, France

Cohabitation in Motion – Learning Safe Interactions Between Pedestrians and Autonomous Agents

Abstract: Artificial Intelligence is often seen as a support system for human activities — easing our tasks and enabling new possibilities. Yet in certain contexts, AI is no longer merely a tool of assistance: it becomes an autonomous agent, capable of interacting — or even conflicting — with humans.

This is particularly evident in industrial environments, where autonomous vehicles share space with pedestrians, especially when crossing logistic or operational zones. In such sensitive scenarios, a central question arises: how can we ensure intelligent, seamless, and safe cohabitation, without disrupting workflow efficiency?
Multi-agent trajectory optimization techniques offer promising avenues, but struggle to capture the complexity of human behavior. Multi-Agent Reinforcement Learning (MARL) introduces a more adaptive approach, capable of learning interactions in dynamic and shared environments. However, these methods also raise new challenges — which will be addressed during the presentation.
The talk will offer a comparative perspective on these approaches, supported by empirical insights drawn from a simulated environment. A fully immersive setup, combining a traffic simulator with a virtual reality-based pedestrian data collection system, will be used to illustrate key scenarios and suggest future directions.
 

Bio: Abdeljalil Abbas-Turki is a Full Professor at the CIAD Laboratory and Head of the Computer Science Department at the University of Technology of Belfort-Montbéliard (UTBM). His research focuses on Intelligent Transportation Systems (ITS), aiming to integrate cutting-edge technologies to enhance transportation efficiency, safety, and sustainability. His work contributes to the development of smart mobility solutions, particularly in connected and autonomous/semi-autonomous vehicles and intelligent infrastructure. Actively collaborating with industry and academic partners, he applies his research to real-world transportation challenges. He notably led the X.icars demonstration at the ITS World Congress 2015, where three connected autonomous vehicles successfully navigated an eight-shaped circuit. Currently, he heads Project X.Hub, which focuses on designing an autonomous tractor for semi-trailers, paving the way for sustainable and automated warehouse logistics.