8th International Conference on Machine Learning for Networking (MLN'2025)
Keynote: Mohsen Guizani, Professor at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, UAE
Title: Artificial Intelligence for Digital Twin in Wireless Systems
Abstract
With the Internet of Things (IoT) transforming our society by connecting the world, future wireless services will focus on improving the quality of life by enabling various applications, such as extended reality, brain-computer interaction, and healthcare. These applications will have diverse performance requirements (e.g., user-defined quality of experience metrics, latency, and reliability) which will be challenging to be fulfilled by existing wireless systems. To meet the diverse requirements of the emerging applications, the concept of digital twins (DT) has been recently proposed and used. A DT uses a virtual representation along with communication technologies (e.g., 6G), computing technologies (e.g., edge computing), security related technologies (e.g., blockchain) and machine learning, to enable smart applications. On the other hand, federated learning (FL) has provided a private platform in many of these applications to protect the data and reduce latency. These smart services/applications rely on efficient computation and communication resources. Furthermore, being able to provide adequate services using these complex systems presents enormous challenges.
In this Keynote, we present a comprehensive overview of DT for wireless systems. We present the fundamental concepts (i.e., design aspects, high-level architecture, and frameworks) of digital twins for wireless systems. Then, we showcase our research activities that will contribute to these efforts and advocate possible solutions using DT models. We provide ways on how to manage the available resources intelligently and efficiently to offer better living conditions for our citizens and provide better services. Finally, we discuss some of our research results and future directions to support a variety of applications relevant to DT for wireless.
Biography
Mohsen Guizani (Fellow, IEEE) received the BS (with distinction), MS and PhD degrees in Electrical and Computer engineering from Syracuse University, Syracuse, NY, USA. He is currently a Professor of Machine Learning at the Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, UAE. Previously, he worked in different institutions in the USA. His research interests include applied machine learning and artificial intelligence, smart city, Internet of Things (IoT), intelligent autonomous systems, and cybersecurity. He was elevated to IEEE Fellow in 2009 and was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science in 2019-2022. Dr. Guizani has won several research awards including the “2015 IEEE Communications Society Best Survey Paper Award”, the Best ComSoc Journal Paper Award in 2021 as well 5 Best Paper Awards from ICC and Globecom Conferences. He is the author of 11 books, more than 1000 publications and several US patents. He is also the recipient of the 2017 IEEE Communications Society Wireless Technical Committee (WTC) Recognition Award, the 2018 AdHoc Technical Committee Recognition Award, and the 2019 IEEE Communications and Information Security Technical Recognition (CISTC) Award. He served as the Editor-in-Chief of IEEE Network and is currently serving on the Editorial Boards of many IEEE Transactions and Magazines. He was the Chair of the IEEE Communications Society Wireless Technical Committee and the Chair of the TAOS Technical Committee. He served as the IEEE Computer Society Distinguished Speaker and is currently the IEEE ComSoc Distinguished Lecturer.