Yunhao Liu, ACM Fellow, IEEE Fellow, Chair Professor at Tsinghua University. Yunhao received his B.E. degree in the Department of Automation at Tsinghua University, and an M.S. and a Ph.D. degree in Computer Science and Engineering at Michigan State University. Yunhao received China National Natural Science Award, ACM Presidential Award, CCF Wang Xuan Award, CCF Natural Science Award, CIE Natural Science Award as well as many best paper awards including ACM MobiCom Best Paper Award, ACM SenSys Best Paper Award, and SIGCOMM Best Student Paper Award. He also received ACM SenSys 2023 Test of Time Award and IEEE PerCom 2026 Test of Time Award.

The 6G networks are expected to support a wide range of diverse use cases and applications, along with a significant increase in user data traffic. Artificial intelligence (AI) will be deeply embedded in the design and operation of the networks. Specifically, 6G will transition from an information-centric architecture, which connects people and devices, to intelligence-driven architectures that facilitate seamless data sharing, processing, and mining across devices, the edge, and the cloud within the network. This presentation will examine various aspects of integrating AI into network architecture and operations for intelligent network management and service provisioning. We will introduce a holistic network virtualization architecture designed to support AI functionalities and deliver customized services. Additionally, we will explore meta-learning to address non-stationary system dynamics in network management, with cooperative perception among nearby connected and autonomous vehicles as an application example. We will conclude by discussing the challenges and opportunities associated with network management automation, harnessing the advancements in AI technology.

Weihua Zhuang is a University Professor and a University Research Chair in Electrical and Computer Engineering at University of Waterloo, Canada. Her research focuses on network architecture, algorithms and protocols, and service provisioning in future communication systems. She was the Editor-in-Chief of the IEEE Transactions on Vehicular Technology from 2007 to 2013, General Co-Chair of 2021 IEEE/CIC International Conference on Communications in China (ICCC), Technical Program Chair/Co-Chair of 2017/2016 IEEE VTC Fall, and Technical Program Symposia Chair of 2011 IEEE Globecom. She served as the President of the IEEE Vehicular Technology Society in 2023-2024. Dr. Zhuang is a Fellow of the IEEE, Royal Society of Canada, Canadian Academy of Engineering, and Engineering Institute of Canada.

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.

Nei Kato is a Distinguished Professor with Graduate School of Information Sciences, Tohoku University, Japan. He served as the Dean of the Graduate School from 2021 to 2025. His research areas include computer networking, wireless mobile communications, satellite communications, ad hoc & sensor & mesh networks, UAV networks, AI, IoT, and Big Data. He is the Vice President for publication, IEEE Communications Society. He served as the Editor-in-Chief of IEEE Internet of Things Journal, IEEE Network, IEEE Transactions on Vehicular Technology, and the Vice President for Member and Global Activities, IEEE Communications Society. He is a Clarivate Analytics Highly Cited Researcher, a Fellow of the Engineering Academy of Japan, a Fellow of IEEE, and a Fellow of IEICE.

As Internet of Things (IoT) devices continue to permeate our environments, they generate immense streams of real-world data that have the potential to transform how we deliver critical services—from healthcare and agriculture to transportation, smart grids, and disaster response. At the same time, advances in Artificial Intelligence, particularly Distributed Learning and Deep Learning, are unlocking new possibilities in areas like medical diagnostics, urban intelligence, and predictive analytics by learning from these rich, heterogeneous datasets.

However, a fundamental barrier persists: most deep learning models demand massive computational resources and centralized access to data—requirements typically fulfilled by cloud data centres. This centralized model often introduces latency, bandwidth constraints, and privacy challenges that are incompatible with real-time, context-aware decision-making at the edge.

In response, emerging paradigms like Osmotic Computing propose a more dynamic and adaptive distribution of intelligence—allowing computation to seamlessly flow between cloud, edge, and mobile edge environments. Yet, current approaches fall short in describing how to effectively orchestrate and scale distributed deep learning models across this complex continuum.

This keynote presents a vision for Osmotic Meta-Learning—a new class of resource- and data-aware learning algorithms designed to operate across globally distributed, heterogeneous environments. We will explore the following:

1. The foundational concepts behind Osmotic Computing and its relevance to the future of ambient intelligence.
2. Key research and programming challenges in building and coordinating distributed learning workflows that adapt to resource variability and data locality.
3. A novel approach for training distributed deep learning models on thousands of mid-scale IoT and edge devices worldwide—circumventing the need for traditional GPU-heavy cloud infrastructures.
4. Initial results from our deployment on the UK's largest IoT testbed—the Urban Observatory—which offers a real-world validation environment for scalable, osmotic AI systems.

This talk envisions a shift from siloed AI systems to fluid, collaborative, and context-aware intelligence, capable of learning from—and acting upon—the edge of everything.

Professor Rajiv Ranjan is an Australian-British computer scientist, of Indian origin, known for his research in Distributed Systems (Cloud Computing, Big Data, and the Internet of Things). He is University Chair Professor for the Internet of Things research in the School of Computing of Newcastle University, United Kingdom. He is an internationally established scientist in the area of Distributed Systems (having published about 400 scientific papers). He is a fellow of IEEE (2024), Academia Europaea (2022) and the Asia-Pacific Artificial Intelligence Association (2023). He is also the Founding Director of the International Centre (UK-Australia) on the EV Security and National Edge Artificial Intelligence Hub, both funded by EPSRC. He has secured more than $350 Million CNY (£35 Million+ GBP) in the form of competitive research grants from both public and private agencies. He is an innovator with strong and sustained academic and industrial impact and a globally recognized R&D leader with a proven track record. He serves on the editorial boards of top quality international journals including IEEE Transactions on Computers (2014-2016), IEEE Transactions on Cloud Computing, ACM Transactions on the Internet of Things, The Computer (Oxford University), The Computing (Springer) and Future Generation Computer Systems. He led the Blue Skies section (department, 2014-2019) of IEEE Cloud Computing, where his principal role was to identify and write about the most important, cutting-edge research issues at the intersection of multiple, inter-dependent research disciplines within distributed systems research area including Internet of Things, Big Data Analytics, Cloud Computing, and Edge Computing. He is one of the highly cited authors in computer science and software engineering worldwide (h-index=92+, g-index=400+, and 42000+ Google Scholar citations, h-index=67+ and 21000+ Scopus citations, and h-index=52+ and 12000+ Web of Science citations).

Dr. Minyi Guo is the Zhiyuan Chair Professor of Shanghai Jiao Tong University. His present research interests include parallel/distributed computing, compiler optimizations, big data and cloud computing. He has more than 700 publications in major journals and international conferences in these areas. He received 10 best/highlight paper awards from international conferences including ISCA2024 and ISCA2026. Dr. Guo also got the national science and technology achievement award in 2019. He was Editor-in-Chief of IEEE Transactions on Sustainable Computing and now is the Transactions Operation Chair of IEEE Computer Society. He won 2023 IEEE Edward J. McCluskey Technical Achievement Award for his contributions to the design and realization of resource-efficient cloud computing. He is Fellow of IEEE and CCF.

This talk will introduce the state-of-the-art technologies and future trends of the low-altitude economy, with an in-depth analysis of bottlenecks and core challenges current low-altitude communication networking technologies face. The talk will elaborate on our practical explorations to extend IoT systems into the low-altitude airspace, and present our research on building low-altitude communication infrastructure via low-power wide-area networking (LPWAN) technologies to empower various low-altitude systems and applications.

Dr. Mo Li is a Professor at the Hong Kong University of Science and Technology. His research interests lie in wireless sensing and networking systems, mobile computing and IoT, as well as low-altitude economy. His research led to major impact and has been recognized with highly regarded research awards including ACM SIGMOBILE Test-of-Time Award (2026), SenSys Test-of-Time Award (2022), National Natural Science Award (2011), and numerous best paper awards in major venues including ACM MobiCom and SenSys. He currently serves the Chair of ACM SIGMOBILE and Editor-in-Chief of ACM Transactions on Internet of Things.

He served on the editorial boards of top journals including IEEE/ACM Transactions on Networking, IEEE Transactions on Mobile Computing, and IEEE Transactions on Wireless Communications. Dr. Li was named an ACM Distinguished Member in 2019 and elevated to IEEE Fellow in 2020.