Prof. Fumiyuki Adachi

IEEE Life Fellow

Tohoku University, Japan

Bio: 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 for3G and beyond. He contributed to developing the3G 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 beyond5G/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: Recent Advances of Distributed MU-MIMO and Its Integration with Cellular Architecture: Toward High-Capacity, Resilient, and Energy-Efficient 6G Networks

Speech Abstract: For future 6G systems, there is an increasing demand for highly reliable and ultra-high-rate communications with targets exceeding 1 Gbps per user, even under the constraints of limited bandwidth and transmit power. However, achieving such performance remains a significant challenge due to the fundamental characteristics of wireless channels, namely propagation path loss and multipath fading. To address this challenge, there is a critical need for new wireless technologies that can simultaneously improve both spectral efficiency and energy efficiency. Among the potential solutions, Multi-user Multiple-Input Multiple-Output (MU-MIMO) has emerged as a highly anticipated technology. In particular, distributed MU-MIMO, which utilizes densely distributed transmit and receive antennas,is expected to significantly improve both efficiencies by exploiting shorter communication distances. Furthermore, by integrating cellular architecture into this framework, the scalability of distributed MU-MIMO systems can be ensured, and the system's limited signal processing capacity can be utilized effectively. In this talk, we will introduce the fundamental concept and performance of cellular distributed MU-MIMO technology as a key enabling technology for 6G networks.

Prof. Markus Rupp

IEEE Fellow

Technische Universität Wien, Austria

Bio: Markus Rupp (Fellow, IEEE) received the Dipl.-Ing. degree from the University of Saarbrcken, Germany, in 1988, and the Dr.-Ing. degree from Technische Universitt Darmstadt, Germany, in 1993. Until 1995, he was a Postdoctoral Researcher with the University of California at Santa Barbara, Santa Barbara, CA, USA. From 1995 to 2001, he was with the Wireless Technology Research Department, Nokia Bell Laboratories, Holmdel, NJ, USA. Since 2001, he has been a Full Professor of digital signal processing in mobile communications with Technische Universität Wien.

Speech Title: Digital Twins (DTs) in wireless communications

Speech Abstract: Wireless communication networks are entering an era of unprecedented complexity. With the transition from 5G to 6G, technologies such as massive MIMO, network slicing, non-terrestrial networks (NTN), and integrated sensing and communication (ISAC) are pushing current planning and optimisation methods beyond their limits. Traditional simulation tools—highly successful in the design phase—are no longer sufficient to support real-time operational decisions in rapidly changing environments shaped by mobility, traffic dynamics, and evolving urban infrastructure.

This talk introduces the concept ofDigital Twins (DTs) in wireless communications, highlighting their role as the next evolutionary step beyond classical link-level and system-level simulators. A digital twin is not merely a model, but a continuously updated virtual representation of a live network system, driven by real-time telemetry and measurement feedback. By combining calibrated physical wireless models with operational network abstraction layers, digital twins enable prediction, optimisation, and closed-loop control of real networks. This opens the door to self-healing networks, proactive maintenance, and safe AI training environments—without risking disruption of critical services.The talk will provide an overview of the historical roots of simulation and the emergence of the digital twin paradigm, followed by key use cases including geo-spatial propagation modelling via ray tracing, anomaly detection for predictive maintenance, AI-based resource management, and energy-efficient “green networking” through adaptive sleep modes. Looking ahead toward 6G standardisation, digital twins are expected to evolve from management tools into core architectural elements of autonomous networks, enabling large-scale integration of terrestrial and satellite infrastructures, centimetre-level localisation, and real-time situational awareness.

Finally, open challenges such as computational scalability, uncertainty quantification, the privacy/security of operator data, and stability in closed-loop control will be discussed, outlining promising research directions toward trustworthy, real-time-capable wireless digital twins. 

Prof. Yan Zhang

IEEE Fellow

University of Electronic Science and Technology of China, China

Bio: Yan Zhang is currently a Full Professor with University of Electronic Science and Technology of China, China. His research interests include next-generation wireless networks leading to 6G, green and secure cyber-physical systems. Dr. Zhang is an Editor for several IEEE transactions/magazine. Since 2018, Prof. Zhang has been listed as a Highly Cited Researcher by Clarivate Analytics (i.e., Web of Science). He is Fellow of IEEE, Fellow of IET, elected member of Academia Europaea (MAE), elected member of the Royal Norwegian Society of Sciences and Letters (DKNVS), and elected member of Norwegian Academy of Technological Sciences (NTVA).

Speech Title: Edge Computing Power Networks

Prof. Tian Hong Loh

IEEE Fellow

National Physical Laboratory, U.K.

Bio: Tian Hong Loh (Fellow, IEEE) received the Ph.D. degree in engineering from the University of Warwick, Coventry, U.K., in 2005. Since 2005, he has been with the National Physical Laboratory (NPL), Teddington, U.K., where he is currently the Principal Research Scientist. He leads work at NPL on a wide range of applied electromagnetic metrology research areas to support the telecommunications industry. He is also a Visiting Professor with Surrey University, Guildford, U.K., the President of the International Union of Radio Science (URSI) U.K. Panel, and the Chair of the Measurement Working Group of the European Association on Antennas and Propagation (EurAAP). He holds seven patents, one edited book—Metrology for 5G and Emerging Wireless Technologies (IET, 2021), nine book chapters, and has authored and co-authored over 200 refereed publications. His research interests include 5G/6G communications, smart antennas, small antennas, metamaterials, body-centric communications, wireless sensor networks, electromagnetic compatibility, and computational electromagnetics.

Prof. Shiwen Mao

IEEE Fellow

Auburn University, USA

Bio: Shiwen Mao is a Professor and Earle C. Williams Eminent Scholar Chair, and Director of the Wireless Engineering Research and Education Center (WEREC) at Auburn University. Dr. Mao's research interest includes wireless networks, multimedia communications, smart health, smart grid, and machine learning. His work has been recognized by many research and service awards from the IEEE. He is a Distinguished Lecturer of IEEE ComSoc, the Editor-in-Chief of IEEE Transactions on Cognitive Communications and Networking, and an Associate Editor-in-Chief of IEEE Internet of Things Journal. He is a member-at-large of ComSoc Board of Governors (BOG) (2025-2027), ComSoc Director of Magazines (2026-2027), ComSoc Technical Committee Board Director (2022-2025), and the Vice President of Technical Activities of IEEE Council of RFID (2024-2027). He was the General Chair of IEEE INFOCOM 2022, a TPC Chair of IEEE INFOCOM 2018, and a TPC Vice-Chair of IEEE GLOBECOM 2022. He has served as the General Chair, TPC Chair, or Symposium/Track Chair of numerous IEEE/ComSoc conferences, including INFOCOM, ICC, and Globecom. He is a Fellow of IEEE.

Speech Title:  Cloud Computing Meets Functional Data Analysis for Wireless and Network Intelligence

Speech Abstract: Cloud computing underpins modern data infrastructure and continuously generates high frequency telemetry from IoT sensors, serverless functions, and virtualized resource logs. Similar time varying data streams arise across intelligent transportation systems, wireless sensing platforms, and connected device ecosystems. Such observations are inherently functional in nature, better modeled as smooth trajectories evolving over continuous domains rather than as isolated tabular records. Yet most analytics pipelines remain rooted in discrete machine learning models that overlook temporal continuity, cross trajectory dependence, and latent functional structure. Functional Data Analysis (FDA) provides a principled statistical framework for modeling data at the function level through smoothing, basis representations, and covariance driven dimensionality reduction. Despite its strong theoretical foundations, FDA remains underutilized in large scale computing and sensing systems due to gaps between statistical methodology and engineering deployment. This talk highlights FDA as a unifying modeling paradigm for time varying data, presenting recent work in traffic flow modeling, RF sensing, RFID signal analysis, and device fingerprinting. Across these domains, functional representations demonstrate improved robustness to noise and missing data, enhanced interpretability of temporal dynamics, and stronger cross domain generalization, positioning FDA as a scalable foundation for modern cyber physical analytics.