Plenary Session
Title : Key Enabling Technologies Shaping the Future of Wireless Communications Beyond 5G and 6G
Prof. Xuan Nam Tran
Biography
Prof. Xuan Nam Tran earned his Master of Engineering (M.E.) degree in telecommunications engineering from the University of Technology Sydney, Sydney, Australia, in 1998, and his Doctor of Engineering degree in electronic engineering from The University of Electro-Communications, Japan, in 2003. He is currently serving as the Vice President and Head of the Advanced Wireless Communications Research Group at Le Quy Don Technical University, Hanoi, Vietnam.Prof. Tran’s research focuses on enabling technologies for the next generation of wireless communications, including space-time signal processing, UAV communications, in-band full duplex (IBFD), reconfigurable intelligent surfaces (RIS), and machine learning. His pioneering work has earned him several accolades, including the 2003 IEEE AP-S Japan Chapter Young Engineer Award and co-recipient honors for best papers at prestigious conferences, including the 2012 International Conference on Advanced Technologies for Communications, the 2014 National Conference on Electronics, Communications, and Information Technology, the 8th NAFOSTED Conference on Information and Computer Science (NICS 2021), and the 12th International Conference on Control, Automation and Information Sciences (ICCAIS 2023).Prof. Tran is the founding Chair and current Chapter Chair of the Vietnam Chapter of the IEEE Communications Society. He also holds key national leadership roles, including Chair of the NAFOSTED Scientific Council in Information and Computer Science, Vice Chair of the National Program for High Technology Development, and member of the State Council for Professorship in Electricity, Automation, and Electronics, Vice President of the Radio-Electronics Association of Vietnam. Additionally, he chaired the award selection committee for the prestigious Ta Quang Buu Prize in Science and Technology in 2024.
Prof. Xuan Nam Tran earned his Master of Engineering (M.E.) degree in telecommunications engineering from the University of Technology Sydney, Sydney, Australia, in 1998, and his Doctor of Engineering degree in electronic engineering from The University of Electro-Communications, Japan, in 2003. He is currently serving as the Vice President and Head of the Advanced Wireless Communications Research Group at Le Quy Don Technical University, Hanoi, Vietnam.Prof. Tran’s research focuses on enabling technologies for the next generation of wireless communications, including space-time signal processing, UAV communications, in-band full duplex (IBFD), reconfigurable intelligent surfaces (RIS), and machine learning. His pioneering work has earned him several accolades, including the 2003 IEEE AP-S Japan Chapter Young Engineer Award and co-recipient honors for best papers at prestigious conferences, including the 2012 International Conference on Advanced Technologies for Communications, the 2014 National Conference on Electronics, Communications, and Information Technology, the 8th NAFOSTED Conference on Information and Computer Science (NICS 2021), and the 12th International Conference on Control, Automation and Information Sciences (ICCAIS 2023).Prof. Tran is the founding Chair and current Chapter Chair of the Vietnam Chapter of the IEEE Communications Society. He also holds key national leadership roles, including Chair of the NAFOSTED Scientific Council in Information and Computer Science, Vice Chair of the National Program for High Technology Development, and member of the State Council for Professorship in Electricity, Automation, and Electronics, Vice President of the Radio-Electronics Association of Vietnam. Additionally, he chaired the award selection committee for the prestigious Ta Quang Buu Prize in Science and Technology in 2024.
Abstract
In this keynote speech, we will explore the transformative potential of emerging technologies that are set to redefine the landscape of wireless communications beyond 5G and 6G. As the demand for ultra-reliable, high-speed, and low-latency networks grows, technologies such as Full-Duplex Communication, Reconfigurable Intelligent Surfaces (RIS), Unmanned Aerial Vehicles (UAVs), and Multi-Access Edge Computing (MEC) are becoming critical enablers of the next-generation wireless ecosystem. Full-duplex communication promises to double network capacity by allowing simultaneous transmission and reception of data, overcoming one of the fundamental limitations of current wireless systems. RIS will revolutionize network coverage and efficiency by dynamically controlling the propagation of electromagnetic waves, enhancing signal strength and reducing interference, particularly in complex environments. UAVs, with their ability to provide flexible, on-demand connectivity, will play a pivotal role in extending wireless coverage to underserved or remote areas. Meanwhile, MEC brings computation and storage closer to the end user, drastically reducing latency and enabling real-time data processing for applications such as autonomous systems, IoT, and immersive experiences. The convergence of these technologies represents a major leap forward in creating highly adaptive, efficient, and scalable networks. This speech will delve into their individual and combined potential, highlight real-world applications, and discuss the challenges and opportunities they present in shaping the wireless communications of tomorrow.
In this keynote speech, we will explore the transformative potential of emerging technologies that are set to redefine the landscape of wireless communications beyond 5G and 6G. As the demand for ultra-reliable, high-speed, and low-latency networks grows, technologies such as Full-Duplex Communication, Reconfigurable Intelligent Surfaces (RIS), Unmanned Aerial Vehicles (UAVs), and Multi-Access Edge Computing (MEC) are becoming critical enablers of the next-generation wireless ecosystem. Full-duplex communication promises to double network capacity by allowing simultaneous transmission and reception of data, overcoming one of the fundamental limitations of current wireless systems. RIS will revolutionize network coverage and efficiency by dynamically controlling the propagation of electromagnetic waves, enhancing signal strength and reducing interference, particularly in complex environments. UAVs, with their ability to provide flexible, on-demand connectivity, will play a pivotal role in extending wireless coverage to underserved or remote areas. Meanwhile, MEC brings computation and storage closer to the end user, drastically reducing latency and enabling real-time data processing for applications such as autonomous systems, IoT, and immersive experiences. The convergence of these technologies represents a major leap forward in creating highly adaptive, efficient, and scalable networks. This speech will delve into their individual and combined potential, highlight real-world applications, and discuss the challenges and opportunities they present in shaping the wireless communications of tomorrow.
Title : How Generative AI and the Internet of Things Can Complement Each Other
Associate Professor Axel Sikora, Offenburg University, Germany
Biography
Dr. Axel Sikora is an associate professor at Offenburg University, Germany, where he serves as Scientific Director of the Institute of Reliable Embedded Systems and Communication Electronics, a leading R&D institute for IIoT connectivity solutions. He is also deputy director of Hahn-Schickard Association of Applied Research, where he manages the division “Software Solutions”, including several research groups around AI. Dr. Sikora is also engaging in several standardization activities around secure and efficient IIoT connectivity. Since many years, he is serving as chairman of the embedded world Conference, the world’s largest event on the topic. In parallel, he is engaged in some deep-tech spinoff companies.
Dr. Axel Sikora is an associate professor at Offenburg University, Germany, where he serves as Scientific Director of the Institute of Reliable Embedded Systems and Communication Electronics, a leading R&D institute for IIoT connectivity solutions. He is also deputy director of Hahn-Schickard Association of Applied Research, where he manages the division “Software Solutions”, including several research groups around AI. Dr. Sikora is also engaging in several standardization activities around secure and efficient IIoT connectivity. Since many years, he is serving as chairman of the embedded world Conference, the world’s largest event on the topic. In parallel, he is engaged in some deep-tech spinoff companies.
Abstract
It is increasingly accepted that to an important degree, “innovation” is a process of combining pre-existing ideas and technologies in novel ways. Generative AI and the Internet of Things can be seen as one successful example of such “Innovation by Combination” combining two megatrends. The Internet of Things connects anything, anywhere, anytime. Thus, it provides a platform for a truly pervasive and intelligent environment. Artificial Intelligence and most notably Edge AI use this platform and make devices intelligent. However, training AI models for IoT applications can be a challenge, as in many cases, devices come with very limited ressources, are spatially distributed, and sample only smaller amounts of data. Thus, we are often suffering from a “small data challenge”. Generative AI may help to overcome this challenge. The keynote disccusses the manifold IoT applications, which potentially could benefit from Generative AI, shows basic architectures and approaches for such solutions on the different IoT layers, and presents several examples from the community and from the author’s own research.
It is increasingly accepted that to an important degree, “innovation” is a process of combining pre-existing ideas and technologies in novel ways. Generative AI and the Internet of Things can be seen as one successful example of such “Innovation by Combination” combining two megatrends. The Internet of Things connects anything, anywhere, anytime. Thus, it provides a platform for a truly pervasive and intelligent environment. Artificial Intelligence and most notably Edge AI use this platform and make devices intelligent. However, training AI models for IoT applications can be a challenge, as in many cases, devices come with very limited ressources, are spatially distributed, and sample only smaller amounts of data. Thus, we are often suffering from a “small data challenge”. Generative AI may help to overcome this challenge. The keynote disccusses the manifold IoT applications, which potentially could benefit from Generative AI, shows basic architectures and approaches for such solutions on the different IoT layers, and presents several examples from the community and from the author’s own research.
Title : “AI for Science and Systems for AI”
Prof. Rajkumar Kettimuthu
Argonne National Laboratory
The University of Chicago
United States of America
The University of Chicago
United States of America
Biography
Dr. Rajkumar Kettimuthu is a Computer Scientist and Group Leader at Argonne National Laboratory, a Senior Scientist at The University of Chicago and a Senior Fellow at Northwestern University. His research interests include AI for science, advanced wired and wireless communications for science, and Quantum networks. Data transfer protocol and tools developed by him and his colleagues at Argonne have become the de facto standard for file transfers in many science environments. With 60K+ installations in six continents, these tools perform 50M+ file transfers & move 5 Petabytes+ of data every day. AI for science tools developed by his team at Argonne are being used in many science environments. These tools have been highlighted by top scientific journals and have won multiple awards at prestigious venues. He has co-authored 150+ peer-reviewed articles most of which appeared in premier journals and top IEEE/ACM conferences, and several of which won best paper award. His work has featured in 20+ news articles. He is a recipient of the prestigious R&D 100 award. He is a distinguished member of ACM and a senior member of IEEE.
Dr. Rajkumar Kettimuthu is a Computer Scientist and Group Leader at Argonne National Laboratory, a Senior Scientist at The University of Chicago and a Senior Fellow at Northwestern University. His research interests include AI for science, advanced wired and wireless communications for science, and Quantum networks. Data transfer protocol and tools developed by him and his colleagues at Argonne have become the de facto standard for file transfers in many science environments. With 60K+ installations in six continents, these tools perform 50M+ file transfers & move 5 Petabytes+ of data every day. AI for science tools developed by his team at Argonne are being used in many science environments. These tools have been highlighted by top scientific journals and have won multiple awards at prestigious venues. He has co-authored 150+ peer-reviewed articles most of which appeared in premier journals and top IEEE/ACM conferences, and several of which won best paper award. His work has featured in 20+ news articles. He is a recipient of the prestigious R&D 100 award. He is a distinguished member of ACM and a senior member of IEEE.
Abstract
Deep learning techniques use multi-layer (“deep”) neural networks (DNNs) to learn representations of data with multiple levels of abstraction. These techniques can discover intricate structure in a dataset by using a back-propagation algorithm to set the internal parameters that are used to transform data as they flow between network layers. We have applied deep learning methods to accelerate various science applications including ones from light sources and climate science. In this talk, I will provide an overview of this work. We have also developed systems such as FairDMS (Findable, Accessible, Interoperable and Reusable Data and Model Service) and FreeTrain (A Framework to Utilize Unused Supercomputer Nodes for Training Neural Networks) to accelerate deep learning training. I will discuss these systems as well in my talk.
Deep learning techniques use multi-layer (“deep”) neural networks (DNNs) to learn representations of data with multiple levels of abstraction. These techniques can discover intricate structure in a dataset by using a back-propagation algorithm to set the internal parameters that are used to transform data as they flow between network layers. We have applied deep learning methods to accelerate various science applications including ones from light sources and climate science. In this talk, I will provide an overview of this work. We have also developed systems such as FairDMS (Findable, Accessible, Interoperable and Reusable Data and Model Service) and FreeTrain (A Framework to Utilize Unused Supercomputer Nodes for Training Neural Networks) to accelerate deep learning training. I will discuss these systems as well in my talk.
Title : “6G NTN for Ubiquitous Connectivity from Network Perspective”
Dr. Namseok Ko
Director in Electronics and Telecommunication Research Institute (ETRI)
Korea
Biography
Dr. Namseok Ko earned his M.S. and Ph.D. from KAIST in 2000 and 2015, respectively. Currently, he directs the Mobile Core Network Research Section at the Electronics and Telecommunication Research Institute (ETRI) and is an associate professor at the University of Science and Technology (UST). He holds positions as Vice-Chair of SG11 at ITU-T, and serves as Vice-Chair of the Technology Committee and Chair of the Network Technology Work Group at Korea’s 6G Forum. Since joining ETRI in 2000, he has contributed to several R&D projects, notably in 5G mobile core technologies, and currently leads projects focused on 6G network architecture. His research interests encompass 5G/6G mobile core network architecture and enabling technologies, including network programmability, networking and computing convergence, and non-terrestrial networks.
Dr. Namseok Ko earned his M.S. and Ph.D. from KAIST in 2000 and 2015, respectively. Currently, he directs the Mobile Core Network Research Section at the Electronics and Telecommunication Research Institute (ETRI) and is an associate professor at the University of Science and Technology (UST). He holds positions as Vice-Chair of SG11 at ITU-T, and serves as Vice-Chair of the Technology Committee and Chair of the Network Technology Work Group at Korea’s 6G Forum. Since joining ETRI in 2000, he has contributed to several R&D projects, notably in 5G mobile core technologies, and currently leads projects focused on 6G network architecture. His research interests encompass 5G/6G mobile core network architecture and enabling technologies, including network programmability, networking and computing convergence, and non-terrestrial networks.
Abstract
The advent of 6G networks heralds a new era of ubiquitous connectivity, with Non-Terrestrial Networks (NTN) playing a pivotal role in bridging the global digital divide. This talk focuses on the integration of NTNs into the 6G ecosystem, emphasizing the architectural, operational, and standardization challenges from a network perspective. We will explore how NTNs enable seamless connectivity across diverse environments—urban, rural, maritime, and aerial—by complementing terrestrial networks. The presentation delves into key topics in NTN-enabled 6G architectures. Through technical insights and case studies, this session aims to illustrate the transformative potential of 6G NTNs in ensuring global connectivity, shaping a truly inclusive, hyper-connected future.
The advent of 6G networks heralds a new era of ubiquitous connectivity, with Non-Terrestrial Networks (NTN) playing a pivotal role in bridging the global digital divide. This talk focuses on the integration of NTNs into the 6G ecosystem, emphasizing the architectural, operational, and standardization challenges from a network perspective. We will explore how NTNs enable seamless connectivity across diverse environments—urban, rural, maritime, and aerial—by complementing terrestrial networks. The presentation delves into key topics in NTN-enabled 6G architectures. Through technical insights and case studies, this session aims to illustrate the transformative potential of 6G NTNs in ensuring global connectivity, shaping a truly inclusive, hyper-connected future.
Online Presentation Link Address
https://hongik.webex.com/meet/jsnbs
Number: 578 788 779
Number: 578 788 779