Keynote  Speaker 1 : Ala' Khalifeh - The Internet of Things and Artificial Intelligent Integration and Applications

Prof. Ala’ Khalifeh currently works as a Professor of Computer Engineering at the School of Computing at the German Jordanian University (GJU). Prof. Khalifeh received the prestigious Fulbright Scholarship in 2005, which enabled him to pursue his doctoral degree from the University of California-Irvine in the United States of America. In September 2021, Prof. Khalifeh became a Fellow of the Innovation Leaders Fellowship (LIF) Program run by the Royal Academy of Engineering - UK. Prof. Khalifeh's research focuses on emerging technologies including the Internet of Things, artificial intelligence, datal analytics, cloud computing and wireless sensor networks. He has published more than 150 research papers in international conferences and indexed journals. Recognizing Prof. Khalifeh’s research impact, he recently was recognized by Stanford-Elsevier Ranking of Top 2% Top-cited Researchers Includes in 2023 and 2024.

Abstract: The integration of the Internet of Things (IoT) and Artificial Intelligence (AI) presents invaluable opportunities for revolutionizing various aspects of our lives and shaping the future of technology. By combining these two cutting-edge technologies, we can unlock a myriad of potential applications in real-life scenarios that can enhance efficiency, optimize processes, and improve overall user experiences. From smart homes and autonomous vehicles to healthcare systems and industrial automation, the seamless integration of IoT and AI opens a new world of possibilities for innovation and advancement in diverse fields. Through this integration, we can harness the power of connected devices, data analytics, and intelligent algorithms to create transformative solutions that address complex challenges and drive progress in our increasingly digital world. In this talk, we will shed light on the myriad applications and scenarios that utilizes both IoT and AI technologies while discussing the challenges faced with these technologies and the potential solutions.

Keynote  Speaker 2 : Iacovos Ioannou - Brains at the Edge: A BDIx-Driven DAI Framework for Self-Organizing 5G/6G

Dr. Iacovos Ioannou is an Assistant Professor at EUC. He earned his BSc in Computer Science from the University of Cyprus in 2006 and an MSc in Information Security from the Open University of Cyprus. He received his PhD in 2021 from the University of Cyprus and is also a researcher with the CYENS Centre of Excellence in the SNS MRG. His research focuses on 5G/6G and beyond, with emphasis on D2D communication and cell-free networks, leveraging AI, ML, DAI and mini power grids.

Abstract: In this keynote, I will present a unified BDIx-driven distributed AI framework that brings autonomous, explainable intelligence to the very edge of 5G/6G networks and nano-grid energy systems. Building on our work in the ADROIT-6G project, I will demonstrate how BDIx agents—combining beliefs, desires, intentions, and explicit “why” explanations—can orchestrate device-to-device connectivity, spectrum, and power resources in real-time, under uncertain and highly dynamic conditions. By embedding these agents into edge and near-edge nodes, we move from static configurations and rigid policies to a living, adaptive control layer that can learn, reason, and justify its actions while respecting latency, reliability, and energy constraints.

The talk then extends this intelligence from communication networks into nano-grid and micro-grid energy management, treating each nano-grid as a “prosumer” agent that must balance local renewables, storage, EV charging and critical loads. I will explain how ANFIS-based plan libraries, linear programming, and swarm-based optimization (PSO) work together with BDIx to co-optimize power flows, costs, and emissions across multiple interacting nano-grids. Using results from detailed simulations and real-world use cases, I will highlight the practical benefits—reduced energy bills, more resilient grids, and greener operations—as well as the broader vision: a unified, AI-driven regional innovation ecosystem where 6G connectivity and sustainable energy infrastructures co-evolve and reinforce each other.

Keynote  Speaker 3 : Joannes Sam Mertens - Distributed AI for Vehicular Networks: Enabling Efficient and Privacy-Preserving Intelligence

Dr. Joannes Sam Mertens is an Assistant Professor at the University of Catania, Italy. He earned his Bachelor’s and Master’s degrees in Electronics and Communication Engineering from SSN College of Engineering, India, in 2017 and 2019, respectively, and received his Ph.D. in 2022 from the University of Catania. His research focuses on machine learning for infrastructureless and intelligent networks, with applications in vehicular communication, smart mobility, and wireless sensor networks. He has contributed to several European and regional research projects, including SAMOTHRACE, COG-LO, SAFE-DEMON, Cycleshield and DELIAS, and has published in leading IEEE and Elsevier journals on topics such as Distributed Machine Learning, Intelligent Transportation Systems and Digital Twins.

Abstract: Vehicular networks are rapidly evolving into distributed learning environments, where vehicles continuously generate valuable local data that can enhance collective intelligence, if shared efficiently and securely. This keynote focuses on communication-efficient and privacy-preserving distributed learning frameworks that enable vehicles and Road Side Units to collaboratively train AI models without sharing raw data. By leveraging techniques based on Federated Learning and Gossip-based model exchange, vehicles can adaptively share only the most relevant model updates, reducing bandwidth consumption while preserving privacy. The talk will explore mechanisms for layer-wise update selection and adaptive communication strategies, demonstrating how these techniques balance accuracy and privacy.  Finally, practical use cases such as driver behavior profiling and anomaly detection will be presented to illustrate the potential of the efficient collaborative learning techniques in vehicular networks.

Keynote  Speaker 4 : Ramanathan Lakshmanan - Theoretical Foundations of Fog and Edge Computing: Models, Algorithms, and Challenges

Ramanathan L is a seasoned academician with over 18 years of teaching experience. He holds a Ph.D. in Computer Science and Engineering from VIT University, Vellore, India, an M.E. in Computer Science from Sathyabama University, Chennai, India, and a B.E. in Computer Science & Engineering from Bharathidasan University, Tiruchirappalli, India. Currently, he serves as a Professor at VIT University, Vellore, India. His research expertise spans Data Science, Cyber-Physical Systems, Fog and Edge Computing, Cloud Computing, Virtualization, Big Data Classification, IoT and AI&ML. With a strong publication record in international journals and conferences, Ramanathan is also an editorial board member and reviewer for several prominent journals and conferences. His ongoing research focuses on predictive analytics, classification, Clustering and Optimizations. He is an active member of professional bodies like IACSIT, CSI, ACM, IEEE (WIE), and ACEEE, and holds key positions as Associate Editor for the Journal of Network: Computation in Neural Systems and Editorial Advisory Board Member for the Journal of Integrated Science and Technology.