Prof. Fumiyuki Adachi, IEEE Life Fellow
Tohoku University, Japan
Fumiyuki Adachi (Life Fellow, IEEE) received the B.S. and Dr. Eng. degrees in electrical engineering from Tohoku University, Sendai, Japan, in 1973 and 1984, respectively. In April 1973, he joined the Electrical Communications Laboratories of NTT and started mobile communications research. From July 1992 to December 1999, he was with NTT DOCOMO, leading a research group on wideband/broadband wireless access for 3G and beyond. He contributed to developing the 3G air interface standard, known as W-CDMA. Since January 2000, he has been with Tohoku University, Sendai, Japan. He is currently researching resilient wireless communication technology to realize beyond 5G/6G systems as a Specially Appointed Research Fellow/Professor Emeritus at the International Research Institute of Disaster Science (IRIDeS), Tohoku University. His research interests are in the areas of wireless signal processing and networking, including multi-access, equalization, antenna diversity, cooperative transmission, channel coding, and radio resource management.
Speech Title: Building Green and Resilient Radio Access Network (RAN) for 6G Systems
Abstract: Research activities aimed at advancing mobile communications for the 6G era are currently being intensified worldwide. Efficient utilization of mmWave and sub-6GHz bands is essential to address the rapid growth in mobile data traffic. However, mmWave band has serious disadvantages, such as high propagation path loss and frequent blockage, due to its strong rectilinear propagation characteristics. One promising solution that turns the disadvantages of the mmWave band into advantages is to build a user-centric radio access network (RAN) based on distributed MIMO. As mobile communication systems have become a critical infrastructure in our modern society, it will be extremely important in the 6G era to build green and resilient RAN. This can be achieved by introducing reconfiguration capabilities into user-centric RAN. Furthermore, the power consumption of each radio unit (RU) is significantly reduced due to the short communication distance, enabling user-centric RAN to utilize renewable energy and and thereby realizing green RAN. This will enable local production and consumption of renewable energy, accelerating its utilization. This talk will introduce a framework of reconfigurable user-centric RAN framework based on distributed MIMO for building green and resilient 6G systems.
Prof. Geoffrey Ye Li, Fellow of Royal Academy of Engineering, IEEE Fellow, IET Fellow
Imperial College London, UK
Geoffrey Ye Li, FREng (Fellow of Royal Academic of Engineering) and Fellow of IEEE, is a Chair Professor at Imperial College London, UK. Before joining Imperial in 2020, he was a Professor at Georgia Institute of Technology, USA, for 20 years and a Principal Technical Staff Member with AT&T Labs – Research (previous Bell Labs), USA, for five years. He is the first to introduce deep learning to communications in 2016, which has become a popular research area now. He made fundamental contributions to orthogonal frequency division multiplexing (OFDM) for wireless communications, which made him win 2024 IEEE Eric E. Sumner Technical-Field Award. He also won several awards from IEEE Signal Processing, Vehicular Technology, and Communications Societies, including 2019 IEEE ComSoc Edwin Howard Armstrong Achievement Award.
Speech Title: Large AI Models for Wireless Communications
Abstract: The emergence of large language models (LLMs) has revolutionized the AI field, offering unprecedented capabilities in reasoning, generalization, and zero-shot learning. These strengths open new frontiers in wireless communications, where increasing complexity and dynamism demand intelligent and adaptive solutions. This talk explores the role of LLMs in transforming wireless systems across three key directions: adapting pretrained LLMs for core communication tasks, developing wireless-specific foundation models to balance versatility and efficiency, and enabling agentic LLMs with autonomous reasoning and coordination capabilities. We highlight recent advances, practical case studies, and the unique benefits of LLM-based approaches over traditional methods. Finally, we outline open challenges and research opportunities.
Prof. Nei Kato, Fellow of The Engineering Academy of Japan, IEEE Fellow
Tohoku University, Japan
Nei Kato is a full professor and the Dean with Graduate School of Information Sciences(GSIS) and was the Director(2015-2019) of Research Organization of Electrical Communication(ROEC) and the Strategic Adviser(2013) to the President, Tohoku University. He has been engaged in research on computer networking, wireless mobile communications, satellite communications, ad hoc & sensor & mesh networks, UAV networks, smart grid, AI, IoT, Big Data, and pattern recognition. He has published more than 500 papers in prestigious peer-reviewed journals and conferences(Google Scholar citation 28000, h-index 87). He is the Editor-in-Chief of IEEE Internet of Things Journal, the Fellow Committee Chair of IEEE Vehicular Technology Society, Chair of IEEE Communications Society Sendai Chapter, and the Area Editor of IEEE Transactions on Wireless Communications. He served as the Vice-President (Membership & Global Activities) of IEEE Communications Society(2018-2021), the Editor-in-Chief of IEEE Network Magazine (2015-2017), the Editor-in-Chief of IEEE Transactions on Vehicular Technology(2017-2021), a Member-at-Large onthe Board of Governors, IEEE Communications Society(2014-2016), a Vice Chair of Fellow Committee of IEEE Computer Society(2016), and a member of IEEE Communications Society Award Committee (2015-2017). Nei Kato is a Distinguished Lecturer of IEEE Communications Society and Vehicular Technology Society. He is a Fellow of The Engineering Academy of Japan, Fellow of IEEE, and Fellow of IEICE.
Speech Title: AI-based Digital Communication Network Technologies towards 6G
Abstract: In both academia and industry, the exploration of 6G—a further advanced cellular communication technology—has already begun. As our society becomes increasingly digitalized, hyper-connected, and globally data-driven, future services are anticipated to rely heavily on virtually instantaneous, unlimited wireless connectivity. This presentation will outline the key drivers, challenges, and essential research topics associated with 6G. In particular, I will provide an overview of the cutting-edge technologies such as SIGIN, IRS, DT, MEC and WiGig, spanning aspects from physical/networking layers to new use cases and service enablers.
Prof. Abbas Jamalipour, Fellow of the Institution of Engineers Australia, IEEE Fellow
The University of Sydney, Australia
Abbas Jamalipour is the Chair Professor of Ubiquitous Mobile Networking at The University of Sydney and the Editor-in-Chief, IEEE Transactions on Vehicular Technology. He holds a PhD in Electrical Engineering from Nagoya University, Japan; and is a Fellow of the IEEE, IEICE, Engineers Australia, AIIA, and a Visiting Fellow of the Royal Academy of Engineering. He has authored nine technical books, eleven book chapters, over 650 technical papers, and five patents, all in the field of wireless communications. Dr. Jamalipour was the President (2020-21), Executive Vice-President (2018-19), and has been an elected voting member of the Board of Governors of the IEEE Vehicular Technology Society since 2014. Previously, he served as the Editor-in-Chief IEEE Wireless Communications, Vice President-Conferences, and a member of Board of Governors of the IEEE Communications Society. He is on the editorial board of the IEEE Access, member of the Advisory Board of IEEE Internet of Things Journal, and an editor for several other journals. He is the recipient of several prestigious awards such as the IEEE ComSoc Harold Sobol Award, the IEEE ComSoc Best Tutorial Paper Award, as well as over fifteen Best Paper Awards.
Speech Title: Generative AI-Based Secured Wireless Communications for Low-Altitude Economy Networks
Abstract: Low-Altitude Economy Networks (LAENets) are envisioned to be a significant enabler of commercial and social activities, offering low altitude services such as package deliveries and medical supplies in emergency situations. Due to their multifaceted control mechanisms and ever-changing operational factors, LAENets are inherently more complex and vulnerable to security threats than traditional terrestrial networks. As applications of LAENet continue to expand, the robustness of these systems becomes crucial. In this talk, challenges and opportunities in the use of LAENets over wireless channel in terms of security and quality of service will be discussed. A new framework also will be introduced that can demonstrate effectiveness by optimizing beamforming under uncertainties. The talk will highlight the significant potential of GenAI in strengthening LAENet robustness for future applications.
Prof. Ke Guan, Life Fellow RSA
Beijing Jiaotong University, China
Dr. Ke Guan is aFullProfessor at the State Key Laboratory of Advanced Rail Autonomous Operation and the School of Electronic and Information Engineering, Beijing Jiaotong University.In 2024, he was elected aLife Fellow of the Royal Society for Arts, Manufactures and Commerce (Life FRSA).In 2016, he was awarded a Humboldt Research Fellowship. From February 2023 to July 2023, he was a Guest Professor at Technische Universitaet Wien, Austria. He is the major contributor of the clutter loss model in ITU-R P. 2108 and the THz channel model in IEEE 802.15.3d-2017. He has authored/coauthored two books and five book chapters, more than 200 journal and conference papers, and more than 20 patents. His current research interests include the digital twinning of electromagnetic environments in various complex scenarios based on ray-tracing and machine learning. His project TwinSWAN won the 2024 IET Excellence and Innovation Awards. His papers received 14 Best Paper Awards, including the IEEE Vehicular Technology Society Neal Shepherd Memorial Best Propagation Paper Award in 2019 and 2022. He is Beijing Jiaotong University's contact person for 3GPP and ETSI and a member of the IEEE VTS Propagation Committeeand theIEEE AP/S TC on Propagation and Scattering.
Speech Title: HyperRT: Synthesizing Ray-Tracing and AI for Real-time Wireless Digital Twins
Abstract: Smart future requires a fully connected world and provide a high data rate and dependable wireless connectivity for all intelligent devices and services, in terms of communications, sensing, and localization. In response to these requirements, highly accurate channel data need to be realized in various scenarios at all frequency bands. This paper presents the recent progress on hyper ray tracing for high-fidelity channel modeling, which is also a key enabler for smart wireless environments. To begin with, electromagnetic (EM) property and propagation mechanism libraries need to be built for various materials at different bands, from propagation mechanism measurements. Then, through extensive simulations using a high-performance ray tracing platform, realistic channel data can be obtained for communication channels in challenging conditions and multi-band sensing signals. Moreover, machine learning models for super-resolution wireless channel characteristics are presented to show how artificial intelligence can help transferring from high-performance ray tracer to hyper ray tracer in terms of increasing the efficiency of generating channel data while keeping high fidelity. Last but not least, some demos are shown that in the future, hyper ray tracer is promising to offer complete, real-time, accurate, and reliable multipath propagation data that projects the EM environment of the physical world in all aspects to the cyber space.