IEEE MSN 2026 Workshop on Embodied AI and Agnetic AI for Zero-Touch 6G Network

Workshop Organizers:

Prof. Haotong Cao
Nanjing University of Posts and Telecommunications China
Email: haotong.cao@njupt.edu.cn

Dr. Bintao Hu
Xi'an Jiaotong-Liverpool University, China
Email: Bintao.Hu@xjtlu.edu.cn

Dr. Jincheng Dai
Beijing University of Posts and Telecommunications, China
Email: daijincheng@bupt.edu.cn

Dr. Junwei Zhang
Communication University of China, China
Email: jwzhang@cuc.edu.cn

Prof. Yang Yang
Shanghai Center of the Hong Kong University of Science and Technology, China
Email: yangyangsh@ust.hk

Prof. Shugong Xu
Xi'an Jiaotong-Liverpool University, China
Email: Shugong.Xu@xjtlu.edu.cn

Short Biography of Organizers:

Prof. Haotong Cao (Member, IEEE, Senior Member, CIC) received the B.S. Degree in Communication Engineering from Nanjing University of Posts and Telecommunications (NJUPT) in 2015. He received the Ph.D. Degree from NJUPT, China, in 2020. He was a visiting scholar of Loughborough University, U.K. in 2017. He was the PostDoc in the Hong Kong Polytechnic University, Hong Kong, China, from 2020 to 2023. He is currently with Nanjing University of Posts and Telecommunications, China. He has served as the TPC member of multiple IEEE conferences, such as IEEE ICC, IEEE Globecom. He has published multiple technical papers since 2016, such as IEEE TII, IEEE TITS, IEEE IoT-J, IEEE TVT, IEEE TNSM, IEEE TNSE, IEEE NETWORK, IEEE CL, IEEE WCL, (Elsevier) Computer Networks, (Elsevier) Computer Communications, IEEE INFOCOM, IEEE ICC and IEEE Globecom. His research interests include 6G networks, SDN, NFV.

 

Dr. Bintao Hu (Member, IEEE) is an Assistant Professor at the School of Internet of Things, Xi'an Jiaotong-Liverpool University, Suzhou, China. He received his B.Eng. degree in telecommunications engineering from Xiangtan University, Xiangtan, China, in 2015, M.Sc. degree in Data Communications in 2017 and Ph.D. degree in Electronic and Electrical Engineering in 2022, both from the University of Sheffield, UK. He attended the European Commission Decade project with Ranplan, Barcelona, Spain, in 2018. He received the best paper award in EAI 2025, the best oral presentation award in IEEE/ACIS ICIS 2023. He served as a Chair/Co-Chair of many international workshops such as IEEE WCNC 2026, IEEE VTC2024-2026, IEEE/CIC 2025, etc. He served as a TPC for many conferences such as IEEE VTC, IEEE WCNC, IEEE PIMRC, etc. He also served as a reviewer for many journals, such as IEEE TMC, IEEE IoTJ, IEEE TCCN, IEEE TCC, IEEE TNSE, IEEE TVT, IEEE TCOM, etc. His current research interests include ISAC, edge intelligence, low-altitude networks, AI, etc.

 

Prof. Jincheng Dai (Member, IEEE) received the B.S. and Ph.D. degrees from Beijing University of Posts and Telecommunications (BUPT), Beijing, China, in 2014 and 2019, respectively. He is currently an Associate Professor with the School of Artificial Intelligence and the Key Laboratory of Universal Wireless Communications, Ministry of Education, BUPT. His research interests include AI for coding and communications. Dr. Dai has been selected for Beijing Nova Program, China Association for Science and Technology's (CAST) Young Elite Scientists Sponsorship Program, and the Xiaomi Young Scholars Program. As a core contributor, he has received the First-Class Natural Science Award of Chinese Institute of Electronics. He has received several accolades, such as the Excellent Science and Technology Paper Award from CAST.

 

Dr. Junwei Zhang (Member, IEEE) is a Lecturer at the School of Information andCommunication Engineering, at Communication University of China. He received his B.S. degree from the Dalian Maritime University, Dalian, China, in 2016, his M.S. degree and Ph.D. degree from the University of Sheffield, Sheffield, U.K., in 2018 and 2022, respectively. He served as a Co-Chair of IEEE SiPS 2025 and served as a member of the technical committee for many conferences such as IEEE VTC-Fall 2025 and IEEE VTC-Spring 2025. He also served as a reviewer for many journals and international conferences, such as IEEE Transactions on Signal Processing, IEEE Transaction on Wireless Communications and IEEE Antenna and Wireless Propagation Letters. He joined Communication University of China in 2022 and focuses on the key enabling technologies of 6G, including Integrated Sensing and communication (ISAC) and movable antenna array design.

 

Prof. Yang Yang (Fellow, IEEE) received the B.S. and M.S. degrees in Radio Engineering from Southeast University, Nanjing, China, in 1996 and 1999, respectively, and the Ph.D.degree in Information Engineering from the Chinese University of Hong Kong, Hong Kong, China, in 2002. He is currently the Dean of the Shanghai Center, Hong Kong University of Science and Technology (HKUST), Hong Kong, China. He is also an adjunct professor with the Department of Broadband Communication at Peng Cheng Laboratory, and the Chief Scientist of IoT at Terminus Group, China. Before joining HKUST, he has held faculty positions at the Chinese University of Hong Kong, China; Brunel University, U.K.; University College London (UCL), U.K.; CAS-SIMIT, China; ShanghaiTech University, China; and HKUST (Guangzhou), China. Yang's research interests include multi-tier computing networks, 5G/6G systems, AIoT technologies and applications, and advanced wireless testbeds. He has published more than 380 papers and filed more than 120 technical patents in these research areas. He was the Chair of the Steering Committee of Asia-Pacific Conference on Communications (APCC) from 2019 to 2021. He has served the IEEE Communications Society as the Chair for 5G Industry Community and Chair for Asia Region at Fog/Edge Industry Community.

 

Prof. Shugong Xu (Fellow, IEEE) graduated from Wuhan University, Wuhan, China, in 1990, the master's degree in pattern recognition and intelligent control and the Ph.D. degree in EE from Huazhong University of Science and Technology, Wuhan, in 1993 and 1996, respectively. He is currently a Full Professor and the AVP-R with Xi'an Jiaotong-Liverpool University, Suzhou, China. He was the Center Director and the Intel Principal Investigator with the Intel Collaborative Research Institute for Mobile Networking and Computing, prior to December 2016, when he joined Shanghai University, Shanghai, China, as a Full Professor. Before joining Intel Labs in September 2013, he was a Research Director and the Principal Scientist with the Communication Technologies Laboratory, Huawei Technologies, Shenzhen, China. He was also the Chief Scientist and PI for the China National 863 project on End-to-End Energy Efficient Networks. He was one of the cofounders of the Green Touch Consortium together together with Bell Labs, Murray Hill, NJ, USA. Prior to joining Huawei in 2008, he was with Sharp Laboratories of America, Vancouver, WA, USA, as a Senior Research Scientist. Before that, he conducted research as a Research Fellow with the City College of New York, New York, NY, USA; also with Michigan State University, East Lansing, MI, USA; and also with Tsinghua University, Beijing, China. His current research interests include machine learning, pattern recognition, as well as ISAC in wireless communication systems. Prof. Xu is also the Winner of the 2017 Award for Advances in Communication from the IEEE Communications Society.

 

Scope and topics of the workshop:

       The realisation of zero-touch 6G networks is vital to support a broad spectrum of applications—from immersive digital experiences to massive-scale Internet of Things (IoT) deployments—through highly automated architectures. These networks employ artificial intelligence (AI), machine learning (ML), and digital twin technologies to self-manage unprecedented system complexity, enabling functions such as self-configuration, selfoptimisation, and self-healing with minimal human intervention. This framework automates key operational tasks, including resource provisioning, network slicing, and security enforcement, thereby ensuring scalability, resilience, and performance in meeting evolving service demands.

       Zero-touch automation in 6G builds upon technologies that extend well beyond those of 5G. Distributed AI and ML models support decentralised and intelligent decision-making, avoiding centralised bottlenecks. Digital twins create real-time virtual representations of physical network infrastructures, allowing operators to validate configurations and anticipate potential failures or security breaches before deployment. To strengthen trust in autonomous operations, 6G frameworks increasingly incorporate explainable AI and large language models capable of producing human-interpretable rationales. In parallel, blockchain mechanisms are being explored to secure decentralised service provisioning and to maintain reputational integrity within multi-provider environments.

       Within this evolving landscape, embodied AI and agentic AI are emerging as foundational enablers for zero-touch 6G networks. Embodied AI refers to intelligent systems that interact with the physical environment through artefacts such as unmanned aerial vehicles, robotic platforms, or mobile edge nodes. These systems perform sensing, communication, and actuation tasks in real time, contributing to closed-loop automation. Agnetic AI, by contrast, emphasises adaptive, context-aware decision-making that operates autonomously—perceiving, learning, deciding, executing, and engaging in collaborative behaviours tailored to specific network scenarios. Together, these two AI paradigms enhance the cognitive and operational capabilities of zero-touch 6G infrastructures.

       The integration of embodied and agentic AI offers tangible improvements in network resource optimisation, system-level performance, and proactive security management. For example, embodied agents can dynamically reposition aerial base stations or edge computing resources in response to fluctuating traffic demands, while agent-based algorithms autonomously adjust communication parameters and spectrum allocation. Looking towards 2026 and beyond, such synergy is expected to simplify the governance of dense, heterogeneous 6G-IoT ecosystems. Preliminary studies suggest that AI-driven orchestration could yield more than a tenfold improvement in energy efficiency relative to centralised legacy approaches. Research also indicates that zero-touch frameworks may reduce mean time to response by approximately 32% and resolution latency by nearly 88%. Although fully operational commercial 6G networks are not yet deployed, experimental testbeds have demonstrated data rates approaching 280 Gbps. Ongoing work is focused on standardising automated ML pipelines for security and developing zero-touch commissioning models tailored to on-demand, cloud-native radio access networks.

       We are seeking original, completed, and unpublished works that are not under review elsewhere, aiming to assemble a collection of high-quality, crosscutting research papers on a variety of topics, which include, but are not limited to:

• Embodied and agnetic AI-enabled integrated communication, sensing, and computing for zerotouch 6G transport networks
• Agnetic AI-driven resource management and optimisation in zero-touch 6G communication infrastructures
• Enhancing cognitive communication capabilities through embodied and agnetic AI in 6G systems
• Design and optimisation of AI-empowered wireless charging systems for embodied agents in 6Genabled IoT environments
• Testbed development and real-world evaluation of embodied AI systems for zero-touch 6G networks
• Agnetic AI-based model design, deployment, and validation for digital twin-enabled zero-touch 6G applications
• Optimisation of detection, positioning, and navigation for aerial embodied agents in zero-touch 6G scenarios
• Swarm intelligence and collaborative behaviours of embodied AI agents for zero-touch 6G application scenarios
• Security and privacy framework design using agnetic AI in zero-touch 6G network operations
• Agnetic AI model lifecycle management for autonomous zero-touch 6G applications
• Architectural and protocol innovations for communication and networking in zero-touch 6G systems

Paper Submission Guidelines:

       All submissions should follow the IEEE 8.5″x 11″Two-Column Format. Each submission can have up to 6 pages. Authors of accepted papers are expected to present their papers at the workshop. All submissions to MSN 2026 must be uploaded to EasyChair: https://easychair.org/conferences/?conf=msn2026

Important Dates:

• Sep. 20, 2026

  Paper Submission

• Oct. 30, 2026

  Author Notification

• Nov. 7, 2024

  Camera-ready

• Dec. 18-20, 2024

  Conference Date