The 3rd International Conference on Advanced Robotics, Control, and Artificial Intelligence (ARCAI 2026)
November 23-26, 2026, Singapore
Keynote Speeches
Professor Dusit Niyato, IEEE Fellow, EiC of IEEE TNSE
Nanyang Technological University
Talk: Toward Edge General Intelligence with Agentic AI and Agentification
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Abstract:
The rapid expansion of sixth-generation (6G) wireless networks and the Internet of Things (IoT) has catalyzed the evolution from centralized cloud intelligence towards decentralized edge general intelligence. However, traditional edge intelligence methods, characterized by static models and limited cognitive autonomy, fail to address the dynamic, heterogeneous, and resource-constrained scenarios inherent to emerging edge networks. Agentic artificial intelligence (Agentic AI) emerges as a transformative solution, enabling edge systems to autonomously perceive multimodal environments, reason contextually, and adapt proactively through continuous perception-reasoning-action loops. In this context, the agentification of edge intelligence serves as a key paradigm shift, where distributed entities evolve into autonomous agents capable of collaboration and continual adaptation. This presentation gives a comprehensive survey dedicated to Agentic AI and agentification frameworks. First, we systematically introduce foundational concepts and clarify distinctions from traditional edge intelligence paradigms. Second, we analyze important enabling technologies, including compact model compression, energy-aware computing strategies, robust connectivity frameworks, and advanced knowledge representation and reasoning mechanisms. Third, we provide representative case studies demonstrating Agentic AI's capabilities in low-altitude economy networks. Furthermore, we identify current research challenges
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Bio:
Dusit Niyato is a President's Chair Professor in the College of Computing & Data Science (CCDS), Nanyang Technological University, Singapore. Dusit's research interests are in the areas of mobile generative AI, edge intelligence, quantum computing and networking, and incentive mechanism design. Currently, Dusit is serving as Editor-in-Chief (EiC) of IEEE Transactions on Network Science and Engineering. He is also the past EiC and current area editor of IEEE Communications Surveys and Tutorials (impact factor 46.7). Dusit is the Associate EiC of IEEE Transactions on Vehicular Technology, area editor of IEEE Transactions on Communications, topical editor of IEEE Internet of Things Journal, lead series editor of IEEE Communications Magazine, topic editor of IEEE Transactions on Services Computing, senior area editor of IEEE Transactions on Information Forensics and Security (TIFS), and ACM Computing Surveys. Dusit is the Members-at-Large to the Board of Governors of IEEE Communications Society for 2024-2026. He is a Fellow of IEEE, IET, and CIC (China Institute of Communications).
Professor Changyun Wen, IEEE Fellow, EiC of IEEE TCPS
Nanyang Technological University
Talk: Decentralized Prescribed-Time Control for Interconnected Systems
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Abstract:
A significant challenge of decentralized control is how to ensure global stability in large-scale interconnected systems by local controllers that employ only local information. Since earlier 1980s, decentralized adaptive control has motivated continued exploration and research of many researchers. However, in the presence of uncertainties and strong interactions, the proposed schemes in this area have generally been limited to achieving stability only over an infinite time horizon, with the elimination of steady-state errors posing a particular challenge. Decades of attempts to enhance the convergence rate of decentralized control schemes have made little progress.
Recently, a methodology termed prescribed-time control has emerged, demonstrating advantages in achieving accelerated convergence and superior disturbance rejection. The core innovation lies in an unbounded time-varying feedback gain, which enables precise control without prior disturbance knowledge and, crucially, allows for a convergence time that is pre-assignable by the designer. Building on this principle, we recently achieved a key breakthrough: not only developed a decentralized prescribed-time control framework for strongly interconnected systems but also solved the long-standing problem of achieving precise control in such systems under disturbances. The details of the proposed approach and established results will be covered in this talk.
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Bio:
Changyun Wen received his B.Eng from Xi’an Jiaotong University, China in July 1983 and Ph.D from the University of Newcastle, Australia in Feb 1990. From August 1989 to August 1991, he was a Research Associate and then Postdoctoral Fellow at the University of Adelaide, Australia. Since August 1991, He has been with Technological University as a lecturer (from 1991), senior lecturer (from 1995), associate professor (from 1999) and full professor (from 2008).
He is a Fellow of IEEE, was a Member of the IEEE Fellow Committee from Jan 2011 to Dec 2013 and a Distinguished Lecturer of IEEE Control Systems Society from Feb 2010 to Feb 2013. He is also a Fellow of the Academy of Engineering, Singapore.
Prof. Wen is the Editor-in-Chief of IEEE Transactions on Industrial Cyber-Physical Systems, a co-Editor-in-Chief of IEEE Transactions on Industrial Electronics (from July 2020), an Associate Editor of Automatica (from Feb 2006) and the Executive Editor-in-Chief of Journal of Control and Decision. He also served as an Associate Editor of IEEE Transactions on Automatic Control from Jan 2000 to Dec 2002, IEEE Transactions on Industrial Electronics (from May 2013 to Jan 2020) and IEEE Control Systems Magazine from 2009 to 2019, respectively. He has been actively involved in organizing international conferences playing the roles of General Chair, Technical Program Committee Chair, Program Committee Member, General Advisor, Publicity Chair and so on. He was the recipient of several awards, including the IES Prestigious Engineering Achievement Award from the Institution of Engineers, Singapore in 2005, Best Paper Award of IEEE Transactions on Industrial Electronics in 2017, Clarivate Analytics Highly Cited Researcher in the field of Engineering yearly from 2020 to 2025, Stanford/Elsevier Top 2% Scientist Worldwide yearly from 2021 to 2025. His main research activities are in the areas of control systems with applications to cyber-physical systems, smart grids and so on.