Prof. Tomoaki Otsuki, Keio University (Japan)

Brief Introduction: Professor Tomoaki Otsuki is currently a Professor in the Department of Information and Computer Science, Faculty of Science and Technology at Keio University. He is a Fellow of IEICE, a Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA), a Senior Member of IEEE, and a Member of the Engineering Academy of Japan. He received his B.E., M.E., and Ph.D. degrees in Electrical Engineering from Keio University in 1990, 1992, and 1994, respectively. He has conducted research at Tokyo University of Science and the University of California, Berkeley. 
His research interests include wireless communications, optical communications, signal processing, and information theory. Professor Otsuki has published over 315 journal papers and more than 540 international conference papers. He has received numerous prestigious awards, including the Inoue Research Award for Young Scientist, the IEEE Asia-Pacific Young Researcher Award, the ETRI Journal’s Best Reviewer Award, and the IEEE Communications Society Outstanding Service Award. He has served as editor and chair for several flagship IEEE journals and international conferences and holds significant global influence in the fields of communications and artificial intelligence.

Speech Title: Semantic Communications Based on Generative AI

Abstract: Semantic communication is a new communication paradigm that aims to efficiently convey the "meaning" of information, unlike traditional digital communication. The concept was first proposed by Weaver in 1949 but was long neglected due to technological limitations. In recent years, however, advances in AI technology have led to the practical application of the necessary basic technology, and research is progressing rapidly. Semantic communication is also attracting attention as a promising technology for intelligent applications after 6G. This paper outlines the basic concepts of semantic communication, the technological progress through Generative AI, application examples, and future challenges. This keynote further presents a cutting-edge semantic communication framework tailored for vehicular communication scenarios, where key information is extracted from camera data and transmitted among vehicles and road infrastructure. The keynote will conclude by outlining open challenges and research directions.

Prof. Tutomu Murase, Nagoya University (Japan)

Brief Introduction: Professor Tsutomu Murase is a Professor at the Graduate School of Engineering, Nagoya University. He is a Fellow of the Institute of Electronics, Information and Communication Engineers (IEICE) and a Member of IEEE. He received his M.E. degree in 1986 and Ph.D. in 2004 from Osaka University. He previously worked at NEC Corporation and served as a visiting professor at the Tokyo Institute of Technology. Professor Murase has long been engaged in research on quality of service (QoS) control and network traffic management for high-performance Internet systems. 
His current interests include wireless network QoS control, traffic control at the MAC, transport, and session layers, and network security. He has published extensively and holds over 90 patents, including several international patents. He has served as a technical program committee (TPC) member for numerous international conferences and has delivered many invited talks

Speech Title: User cooperative mobility for communication quality

Abstract: This research focuses on communication quality control in body-to-body networks (BBNs), particularly in scenarios where multiple wireless body area networks (WBANs) coexist and interfere with each other. Based on the observation that interference and throughput depend on the distance between WBANs, we propose a user cooperative mobility strategy that adjusts user positions to improve BBN performance without modifying existing protocols or hardware. Experimental results show that the proposed strategy can increase BBN throughput by up to 58% while maintaining the required intra-WBAN communication performance, offering a cost-effective and efficient solution for interference mitigation.

Prof. Kai Liu, Chongqing University (China)

Brief Introduction: Professor Kai Liu is currently a Professor at the College of Computer Science, Chongqing University, and also serves at the National Elite Institute of Engineering. He obtained his Ph.D. in Computer Science from City University of Hong Kong and was a visiting scholar at the University of Virginia. He also completed postdoctoral research at Nanyang Technological University, City University of Hong Kong, and Hong Kong Baptist University.His research interests include mobile computing, pervasive computing, autonomous driving, and artificial intelligence. 
He has published more than 70 papers in top-tier (JCR Q1) journals and over 50 papers in IEEE/ACM Transactions. He has received several best paper awards from international conferences, including ICA3PP, IEEE ISPCE-CN, and NCAA. In recent years, he has been included in the Stanford/Elsevier list of the world's top 2% most-cited scientists

Speech Title: Edge Intelligence in Internet of Vehicles: Key Technologies and Applications 

Abstract: Edge intelligence in internet of vehicles (IoV) has received great attention in both academia and industry. However, IoV inherently exhibits features including high heterogeneity, high dynamics, and distributed architecture. These properties, combined with massive data volumes, compute-intensive tasks, and critical resource constraints, result in great challenges on enabling edge intelligence in IoV. This talk focuses on key technologies on enabling connectivity, collaboration, and intelligence in IoV, including emerging service framework via software defined network, resource allocation and task offloading via Vehicle-Edge-Cloud collaboration, and collaborative intelligent applications and system prototypes via vehicular edge computing.

Assoc. Prof. Peng Yu, Beijing University of Posts and Telecommunications (China)

Brief Introduction: Dr. Peng Yu is currently the Deputy Dean of the School of Future and an Associate Professor at the State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications. His research focuses on intelligent and green network management for 5G/6G networks and multimedia communication systems. He has conducted extensive work in the areas of intelligent reflecting surfaces, self-healing network architecture, and the integration of graph neural networks and generative AI. He is committed to developing high-availability and QoS-guaranteed solutions for future networks.

Speech Title: Generative AI-Driven Self-Healing Architecture for 6G  Intellicise Edge Networks

Abstract: Intelligent and efficient fault management is a critical requirement for 6G intellicise edge networks. Existing research primarily focuses on recovery after faults in specific scenarios, which struggles to meet higher quality of service demands. Targeting 6G edge networks, this paper proposes a highly adaptive, modular, and scalable fault self-healing architecture. It leverages graph neural networks (GNNs) for predictive network performance modeling, fault prediction, and proactive task migration, while utilizing generative AI to enable rapid fault response and intelligent fault handling tailored to network scenarios. Experimental results demonstrate that this collaborative AI model-based self-healing architecture effectively reduces fault response time and enhances network service quality.

Research Scienteist Xianfu Chen, Shenzhen CyberAray Network Technology Company Ltd (China)

Brief Introduction: Dr. Xianfu Chen is currently the Chief Research Engineer at Shenzhen CyberAray Network Technology Co., Ltd., and also serves as a professor at the Shanghai Advanced Research Institute, Chinese Academy of Sciences, and Zhengzhou University. He received his Ph.D. with honors from Zhejiang University in 2012 and worked at VTT Technical Research Centre of Finland for over a decade as a Research Scientist and Senior Scientist. 
His research interests include AI-enhanced wireless communication systems, particularly human-level intelligence, semantic reinforcement learning, and 6G-aware network perception and control. He has received the IEEE Communications Society Outstanding Paper Award and the IEEE Internet of Things Journal Best Paper Award, and serves as an editor for several IEEE journals

Speech Title: AI For Wireless: From Simulation To Real

Abstract: As the demand for intelligent wireless communication accelerates, artificial intelligence (AI) emerges as a pivotal enabler for the evolution of sixth-generation (6G) networks. In this talk, we will first address the challenges associated with native-AI 6G systems. Subsequently, we will present our recent research efforts on offline reinforcement learning (RL) aimed at optimizing the age of semantics in an intelligent reflecting surface-aided cooperative relay communication system. Furthermore, the integration of large language models into the elements of RL will be showcased. Finally, the discussion will cover the remaining open issues and future research directions to facilitate the real-world implementation of these cutting-edge AI techniques within 6G wireless networks.

Professor Rui Yin, Hangzhou City University (China)

Brief Introduction: Professor Yin Rui is currently a Professor at Zhejiang University City College and a Senior Member of IEEE. He holds a Ph.D. in Information and Electrical Engineering from Zhejiang University and completed postdoctoral research at the Georgia Institute of Technology. He also serves as a doctoral advisor at Zhejiang University and an expert in engineering education accreditation under China’s Ministry of Education. His main research interests lie in wireless communication systems and communication theory. 
He is the principal investigator of one National Natural Science Foundation project and has completed several national and provincial-level projects. He has participated in national 973 and 863 programs and multiple Huawei cooperative projects. He was awarded the Second Prize of the Zhejiang Science and Technology Progress Award in 2019 and was recognized as a Leading Talent in Scientific and Technological Innovation in Hangzhou.

Speech Title: Towards Decentralized Wireless Communication: Architectures and Enabling Technologies

Abstract: In centralized wireless communication networks, large amounts of data must be transmitted back to central controller for processing, increasing transmission latency and causing severe network congestion. Furthermore, failures in central nodes can lead to widespread communication disruptions. To address these issues, Decentralized networks have been introduce. For example, mobile edge technology moves computing and storage to the edge of the network, reducing data transmission latency; Device-to-device communication technology enables direct communication between devices, improving communication efficiency; Integrated air-space-ground technology integrates multiple communication networks to expand coverage and enhance communication reliability.