Forums

Abstract

Against the backdrop of rapid advances in artificial intelligence, big data, cloud/edge computing, industrial Internet, and digital twins, the industrial sector is undergoing a major transition from automation to intelligence and from experience-driven to data-driven operation. Industrial intelligence can significantly improve production efficiency, product quality stability, and energy utilization, while also enhancing equipment reliability, raising safety levels, and supporting the manufacturing sector’s green and low carbon transformation.
This forum focuses on the frontier developments, theories, and application challenges of industrial intelligence. Distinguished scholars from leading domestic universities will present the latest research in this field and jointly explore how intelligent control and decision making methods can enhance industrial systems’ autonomy, robustness, and safety, providing theoretical support and engineering pathways for the next generation of industrial intelligent transformation.

Chair: Prof. Hua Geng Tsinghua University, China

Biography

Hua Geng received the B.S. degree in electrical engineering from Huazhong University of Science and Technology, Wuhan, China, in 2003 and the Ph.D. degree in control theory and application from Tsinghua University, Beijing, China, in 2008. From 2008 to 2010, he was a Postdoctoral Research Fellow with the Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada. He joined Automation Department of Tsinghua University in June 2010 and is currently a full professor.
His current research interests include advanced control on power electronics and renewable energy conversion systems, AI for energy systems. He has authored more than 300 technical publications and holds more than 30 issued Chinese/US patents. He was the recipient of IEC 1906 Award, IEEE PELS Sustainable Energy Systems Technical Achievement Award. He is the Editor-in-Chief of IEEE Trans. on Sustainable Energy. He served as general chair, track chairs and session chairs of several IEEE conferences. He is an IEEE Fellow and an IET Fellow, convener of the modeling working group in IEC SC 8A.

Abstract

As an important direction in the development plan of China's new generation of artificial intelligence, multimodal intelligent cooperative perception and decision-making is changing the mode of industrial production and social development. Multimodal modeling and decision-making, large models, embodied intelligence, and other technologies will provide new solutions for complex intelligent systems, particularly for industrial production process identification, operating performance assessment, optimization decision-making, monitoring, and fault diagnosis, through deep multimodal information fusion and efficient, dynamic interaction and collaboration with the human-machine environment, thereby enhancing the system's autonomous perception and decision-making capabilities. This forum will gather renowned experts and scholars in multimodal modeling and decision-making, large models, and embodied intelligence. It will focus on the latest theoretical research and technological practices in this field and promote the development of intelligent, green, and high-quality new productivity.

Chair: Prof. Dakuo He Northeastern University, China

Biography

Dakuo He is a professor at Northeastern University and the head of the Innovation Team at Liaoning University. He is currently the Vice Dean of the School of Information Science and Engineering of Northeastern University, a member of the Process Control Special Committee of the Chinese Society of Automation, a member of the Automation Special Committee of the Chinese Society of Non-ferrous Metals, and Deputy Director of the Liaoning Provincial Key Laboratory Cluster of Robotics. He is engaged in research on industrial artificial intelligence and its related disciplinary theories and practical techniques. As the project leader, he has undertaken 5 projects for the National Natural Science Foundation of China, 3 projects for the National Key Research and Development Program, and many cooperative projects of enterprises; as the first completer, he won 1 first prize in Science and Technology Progress of Chinese Association of Automation, and as a key member, he won 1 first, second and third prizes each of Science and Technology Award of China Nonferrous Metals Industry, and 1 first prize of Science and Technology of China Gold Association. He has published more than 100 high-level academic papers, with more than 100 indexed by SCI and EI. He has also participated in the consulting projects of the Chinese Academy of Engineering, and written research reports, including "Research on the development strategy of intelligent optimization manufacturing in the process industries" and "Research on the feasibility and development strategy of genetic mineral processing engineering".

Abstract

Facing increasingly complex application scenarios, enhancing the performance of intelligent systems requires breakthroughs in collaborative optimization and advanced computing. This forum focuses on cooperative control of multi-agent systems, distributed optimization algorithms, and frontier theories in intelligent computing. It highlights how model-driven and data-driven approaches can improve the overall performance, adaptability, and intelligence of such systems. The forum aims to share the latest research progress in collaboration and computing for intelligent systems and to promote innovative applications in robotics, intelligent manufacturing, and related fields.

Chair: Prof. Long Jin Lanzhou University, China

Biography

Long Jin , Professor and PhD supervisor at Lanzhou University, selected for the National High-level Young Talent Program. He has led four projects funded by the National Natural Science Foundation of China (NSFC), one project under the National Key R&D Program, and multiple provincial/ministerial-level projects (including key projects and awards for outstanding young researchers). Since 2020 he has been named each year to Elsevier’s "Highly Cited Chinese Researchers" list. He currently serves on the editorial boards of several top international journals, including IEEE TIE/TIV/TASE/TFS、IEEE/CAA JAS、Neural Networks and others.

Abstract

Autonomous intelligence represents one of the ultimate goals of artificial intelligence, with its core lying in enabling systems to independently accomplish complex decision-making and control tasks through active perception and interaction with the environment. Achieving this goal urgently requires breakthroughs in key technologies such as dynamic environmental perception, human-machine interaction and collaboration, and autonomous decision-making and planning. This forum focuses on innovative developments in automation technology, addressing the theoretical and practical challenges of integrating perception, learning, and control in autonomous systems operating under uncertain conditions.

Chair: Prof. Erchao Li Lanzhou University of Technology, China

Biography

Erchao Li , Professor at Lanzhou University of Technology, Dean of the School of Automation, Gansu Provincial Leading Talent (first tier), member of the Chinese Society for Machine Learning, member of the Chinese Society for Robotics Engineering, and board member of the Industrial Big Data and Intelligent Systems Subcommittee of the Gansu Mechanical Engineering Society.

Abstract

To pioneer a new era of smart healthcare in China and chart a new blueprint for a Healthy China, the "Knowledge- and Data-Driven Intelligent Diagnosis and Treatment High-End Forum" has been inaugurated. As a premier industry gathering in the country, this year's forum maintains the highest standards and caliber, bringing together esteemed academicians, recipients of the National Science Fund for Distinguished Young Scholars, Yangtze River Scholars, and leaders from top-tier research institutions to jointly contribute to this landmark event. The forum centers on two core engines—"knowledge-driven" and "data-driven" approaches—delving into their deep integration and application in disease and health management. A distinctive highlight is the pioneering focus on "Knowledge- and Data-Driven Intelligent Diagnosis and Treatment" as a cutting-edge theme. It aims to apply the latest AI theories, modern signal processing, intelligent decision-making, and feedback mechanisms across the entire clinical workflow—from model-based dynamic disease prediction and intelligent physical intervention to drug dosage regulation, personalized rehabilitation robots, and closed-loop dynamic modulation systems. This initiative drives the transformation of healthcare models from passive, static, and population-based approaches toward proactive, dynamic, and closed-loop interventions, enabling holistic, personalized, and integrated development spanning diagnosis, treatment, and rehabilitation. This convergence of ideas and multidisciplinary exchange will strive to address major clinical challenges, spark groundbreaking technological innovations, and provide core momentum and strategic support for building a globally influential intelligent diagnosis and treatment system.

Chair: Prof. Guanglin Li Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China

Biography

Prof. Guanglin Li , Ph.D., the Director of the Institute of Integrated Technology at the Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences, the Director of the Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence Synergy Systems, and the Founder & Current President of the Shenzhen Artificial Intelligence Society. He previously served as a Postdoctoral Research Fellow at the University of Illinois at Chicago, USA, a Senior Research Scientist at BiotechPlex Biotechnology Company, USA, an Assistant Professor at Northwestern University, USA, and a Senior Research Scientist at the Rehabilitation Institute of Chicago, USA. His main research focuses on neural-machine interfaces, intelligent interaction, and intelligent rehabilitation systems. As the Principal Investigator, he has successively been granted over major national-level research projects, including the National Key R&D Program Projects, the National Major Scientific Research Instrument Projects of the National Natural Science Foundation of China (NSFC), the NSFC Regional Joint Fund Projects, the NSFC Integrated Projects, and the Key-Area R&D Program Projects of Guangdong Province. He has published over 380 SCI papers with an H-index of 54, including 3 papers in Nature, as well as papers in Nature Electronics, Science Advances (2 papers), JAMA, and IEEE journals. He was listed in Stanford University's World's Top 2% Scientists Ranking for 2020/2021/2023/2024 and the 2024 "Lifetime Scientific Impact Ranking". He has obtained/filed more than 210 domestic and international invention patents and utility model patents. Currently, he holds the positions of the Vice Director of the Rehabilitation Engineering Branch of the Chinese Society of Biomedical Engineering and the Director of the Rehabilitation Engineering Branch of the Guangdong Society of Biomedical Engineering.

Abstract

This forum focus on cooperative control and intelligent decision-making technologies—the core engine underpinning the safe, efficient, and low-carbon operation of complex energy systems. Currently, the new energy-dominated power grid structure, the penetration of massive power electronic devices, and the demand for multi-dimensional interactions among generation, grid, load, and energy storage (source-grid-load-storage) have posed disruptive challenges to traditional control paradigms and operational management.
We will conduct an in-depth exploration of how cutting-edge technologies reshape the system landscape: Developing grid-forming control, virtual synchronous generator (VSG), and other novel intelligent algorithms to support the stable integration of high-penetration renewable energy; Investigating high-precision modeling, real-time simulation, and distributed autonomous cooperative control architectures for power-electronicized systems; Constructing cloud/edge computing platforms, energy internet of things (Energy IoT), and data governance systems that enable full-domain perception and intelligent decision-making; Tackling key technologies in multi-space-time cooperative optimization of source-grid-load-storage and intelligent dispatch of virtual power plants (VPPs); Promoting innovative applications of artificial intelligence (AI) in state assessment, fault diagnosis, and resilience enhancement; Empowering distribution network digitalization and flexible interaction with user-side resources; Building resilient defense and proactive security systems to address extreme events. The integration of these technologies marks a paradigm shift in energy systems—from passive response to proactive prediction, autonomous coordination, and intelligent decision-making—driving the formation of an efficient, resilient, and low-carbon closed-loop control system.
This forum sincerely invites experts to present cutting-edge achievements in theoretical breakthroughs, algorithmic innovation, engineering validation, and multi-energy system cooperative design. We aim to spark new ideas that lead the energy industry through ideological collisions, thereby accelerating the construction of a future energy system driven by digitalization and intelligence.

Chair: Prof. Jinhai Liu Northeastern University, China

Biography

Jinhai Liu , Professor of Northeastern University and Vice President of the Institute of Intelligent Electrical Science and Technology, is a Leading Talent in Technological Innovation under the "Xingliao Talents Program". He has long been engaged in research on the safe operation of energy pipelines, and the technologies and systems developed by him have been applied in 25 provinces nationwide (including CNOOC, Sinopec, PetroChina, and China National Pipe Network Group) as well as overseas.
His research fields include industrial intelligence, special robots, and electromagnetic non-destructive testing technology. He has won more than 10 scientific and technological awards, including the Second-Class Prize of the National Scientific and Technological Progress Award; published over 100 papers indexed by SCI; and obtained more than 90 invention patents. He serves as a peer reviewer for the National Natural Science Foundation of China (NSFC) and a panel expert for project evaluation at the Ministry of Science and Technology (MOST). He has presided over and completed more than 30 scientific research projects entrusted by the state, provinces/cities, and enterprises, including projects under the National Key R&D Program, Key Program and Major Project of NSFC, General Program and Young Scientists Fund of NSFC, major sub-projects of the 863 Program, and major enterprise-funded projects.

Chair: Prof. Yanhong Luo Northeastern University, China

Biography

Yanhong Luo , Ph.D. Supervisor National High-level Young Talent. She is a Director of the IEEE PES (China) Smart Grid and Artificial Intelligence Subcommittee and served as Vice Chair of the IEEE Technical Committee on Adaptive Dynamic Programming and Reinforcement Learning (2015–2016). She has published more than 130 academic papers, including 8 ESI Highly Cited Papers and over 70 papers indexed by SCI. She has obtained more than 20 authorized national invention patents.
Her long-term research focuses on adaptive dynamic programming, distributed optimal control of energy internet, high-penetration integration of distributed energy resources, and aggregation and optimal dispatch of virtual power plants. She has undertaken 5 projects funded by the National Natural Science Foundation of China and the National Key R&D Program, as well as more than 20 horizontal research projects from the Ministry of Education and large power enterprises.
She has received many prestigious awards, including the 2015 IEEE SMC Andrew P. Sage Best Transactions Paper Award, the 2022 Best Paper Award of the Guidance, Navigation and Control International Journal, the 2020 Second-Class National Natural Science Award (Ranked 2nd), the 2017 First-Class Natural Science Award of the Chinese Association of Automation, the 2020 First-Class Science and Technology Progress Award of the Chinese Association of Automation, the 2015 First-Class Natural Science Award of Liaoning Province, and the 2025 Gold Medal at the Geneva International Exhibition of Inventions.

Abstract

As the wave of digital transformation sweeps across the globe, the scale and complexity of enterprise information systems have surged dramatically, posing unprecedented challenges to traditional operation and maintenance (O&M) models. Against this backdrop, complex system state perception and intelligent O&M have emerged as a bridge connecting conventional O&M practices with the future intelligent world. These advanced approaches integrate cutting-edge technologies such as big data, large models, artificial intelligence, machine learning, and visualization, aiming to redefine O&M paradigms and create a more efficient, stable, and secure operational environment. This forum seeks to establish an open and collaborative exchange platform, bringing together experts and scholars from fields like large models, artificial intelligence, graphics and imaging, and machine learning. The focus will be on cutting-edge topics in complex system state perception, including state monitoring, performance evaluation, lifespan prediction, diagnostic decision-making, self-healing recovery, and collaborative optimization. By fostering dialogue and knowledge exchange, we aim to explore new paradigms in complex system state perception and intelligent O&M, providing theoretical foundations and practical pathways to support the innovative development of smart manufacturing.

Chair: Prof. Jing Na Kunming University of Science and Technology, China

Biography

Jing Na , Ph.D., the Director of the Institute of Integrated Technology at the Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences, the Director of the Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence Synergy Systems, and the Founder & Current President of the Shenzhen Artificial Intelligence Society. He previously served as a Postdoctoral Research Fellow at the University of Illinois at Chicago, USA, a Senior Research Scientist at BiotechPlex Biotechnology Company, USA, an Assistant Professor at Northwestern University, USA, and a Senior Research Scientist at the Rehabilitation Institute of Chicago, USA. His main research focuses on neural-machine interfaces, intelligent interaction, and intelligent rehabilitation systems. As the Principal Investigator, he has successively been granted over major national-level research projects, including the National Key R&D Program Projects, the National Major Scientific Research Instrument Projects of the National Natural Science Foundation of China (NSFC), the NSFC Regional Joint Fund Projects, the NSFC Integrated Projects, and the Key-Area R&D Program Projects of Guangdong Province. He has published over 380 SCI papers with an H-index of 54, including 3 papers in Nature, as well as papers in Nature Electronics, Science Advances (2 papers), JAMA, and IEEE journals. He was listed in Stanford University's World's Top 2% Scientists Ranking for 2020/2021/2023/2024 and the 2024 "Lifetime Scientific Impact Ranking". He has obtained/filed more than 210 domestic and international invention patents and utility model patents. Currently, he holds the positions of the Vice Director of the Rehabilitation Engineering Branch of the Chinese Society of Biomedical Engineering and the Director of the Rehabilitation Engineering Branch of the Guangdong Society of Biomedical Engineering.

Chair: Prof. Fei Chu China University of Mining and Technology, China

Biography

Fei Chu , Professor at China University of Mining and Technology, has been selected as a national-level high-end young talent, a member of Jiangsu Province's "Six Major Talent Peaks," and included in China University of Mining and Technology's "High-end Talent Plan." He is a Senior Member of the IEEE and the Chinese Association of Automation, serving as a committee member for the Process Control and Fault Diagnosis & Safety Committees of the Chinese Association of Automation, a committee member for the Intelligent Simulation, Optimization, and Scheduling Committee of the Chinese Simulation Society, and a director of the Jiangsu Provincial Automation Society. He also holds the position of Deputy Director of the Jiangsu Provincial Process Control Committee. Additionally, He serves as an Associate Editor (AE) for the Journal of The Franklin Institute, an editorial board member for the Journal of Control and Decision. His primary research areas include: AI-driven intelligent modeling and operational optimization control for complex industrial processes; monitoring, risk assessment, and fault diagnosis of complex systems and equipment operation. He has led three National Natural Science Foundation projects and participated in one key National Natural Science Foundation project. He has also managed nearly 20 provincial, ministerial, and corporate technical commissioning projects. Published two academic monographs, authored nearly 100 academic papers in domestic and international journals and conferences in the fields of artificial intelligence and control, and secured 21 authorized invention patents. Awarded over 10 honors, including the First Prize of Science and Technology Progress Award by the Chinese Association of Automation, the Second Prize of Science and Technology (Invention) by the China Nonferrous Metals Industry Association, the Outstanding Young Flotation Engineer at the China Flotation Conference, the First Young Science and Technology Award by the Jiangsu Provincial Automation Society, the CPCC Academician Zhang Zhongjun Outstanding Paper Award, the Best Paper Award at the International Conference on Unmanned Systems, and the First Prize of National Coal Industry Education and Teaching Achievement Awards.

Chair: Prof. JianDe Wu Yunnan University, China

Biography

JianDe Wu , Professor of Yunnan University. He was selected for the National High-level Talent Support Program, Yunling Scholar, Leading Talent in Industrial Technology of Yunnan Province. Professor Wu concurrently serves as the Director of the Engineering Research Center for Intelligent Systems and Advanced Control in Nonferrous Metals Industry of China, and as Vice Chairman of the Automation Academic Committee of the Nonferrous Metals Society of China.
His research interests include industrial process monitoring and intelligent control, industrial big data analysis and modeling, and industrial equipment health assurance. More than 20 projects have been undertaken, including key initiatives funded by the National Natural Science Foundation of China (NSFC) Regional Joint Fund and major scientific and technological projects in Yunnan Province. Over 70 papers have been published in high-impact journals such as IEEE Transactions, and more than 40 patents have been authorized. Achievements have been recognized with several prestigious awards, including the Second Prize of the National Science and Technology Progress Award, the First Prize of the Yunnan Provincial Science and Technology Progress Award, the First Prize of the Yunnan Provincial Natural Science Award, and the First Prize of the Chinese Association of Automation Natural Science Award.

Abstract

With the rapid advancement of artificial intelligence technology, engineering education is facing unprecedented opportunities and challenges. This forum, themed "AI-Empowered Engineering Education," brings together experts and scholars from the educational and industrial sectors to explore how AI can reshape the model of engineering talent cultivation. The forum will focus on topics such as AI-driven curriculum reform, the construction of intelligent teaching platforms, the supervision and evaluation of teaching quality, and new pathways for the integration of industry and education. The aim is to propel engineering education to keep pace with the times, cultivate versatile engineering talents with innovative capabilities and practical skills, and inject new momentum into industrial development.

Chair: Prof. Qiuye Sun Shenyang University of Technology, China

Biography

Qiuye Sun currently holds the position of Vice President at Shenyang University of Technology and serves as a Doctoral Supervisor. He is a recipient of the Special Government Allowances granted by the State Council of China and has been recognized with numerous prestigious titles and honors, including National High-Level Leading Talent, the Ministry of Education's Master Teacher in Ideological and Political Education, New Century Excellent Talent, and Scientific and Technological Innovation Leader under the 'Xingliao Talent Plan.' As a primary contributor, He has been the recipient of more than ten significant awards, including the National Natural Science Second Prize, the National Scientific and Technological Progress Second Prize, and the Liaoning Provincial Technological Invention First Prize.In addition to his academic roles, he serves as the Secretary-General of the Energy Internet Specialized Committee of the Automation Society and holds positions as an Editorial Board Member for several journals, including IEEE TNNLS, IET CPS: T&A, Acta Automatica Sinica, Proceedings of the CSEE, Control and Decision, among others.

Abstract

Embodied intelligence (EI) represents an advanced form of artificial intelligence (AI) and a concrete manifestation of bio-inspired intelligence. As such, it has been established as an independent academic discipline in leading domestic universities. Bionic robots serve as one of its key practical implementations. With continuous breakthroughs in control theory, robotics, and EI technologies, embodied intelligent robots have become a key intersection of artificial intelligence and robotics research, and are positioned to serve as the ultimate platform for AI applications. Research in such a field center on three core components: perceptual systems, motor control, and cognitive decision-making. Embodied intelligent robots address forward-looking technological needs across four key dimensions and demonstrate significant potential for application in smart manufacturing, medical rehabilitation, assistive care for the elderly and disabled, security, and defense, among other sectors. The pursuit of high-level technological self-reliance has further created new imperatives for advancing the theoretical foundations and technological innovation of embodied intelligent robots. This forum is designed to provide an academic platform for experts, scholars, and professionals in robotics, control systems, computer science, artificial intelligence, instrumentation, mechanical engineering, and related fields to exchange ideas and share the latest technological developments. Its aim is to accelerate the innovative development and practical deployment of intelligent robots across a wide range of scenarios.
This forum brings together leading domestic experts and scholars to share the latest breakthroughs in cutting-edge research and technologies on embodied intelligent robots. It seeks to foster in-depth discussions on academic trends, broaden research perspectives, advance the integration of robotics and embodied intelligence, and accelerate the application of educational achievements in robot control and decision-making.

Chair: Prof. Binrui Wang China Jiliang University, China

Biography

Binrui Wang , Doctor, professor, and doctoral supervisor, the vice-president of China Jiliang University, the discipline leader of the Provincial First-Class Discipline in Control Science and Engineering, a recipient of the Zhejiang Province New Century Excellent Talent Award, a state-sponsored overseas returnee, and the principal investigator of a National Key R&D Program of China. His main research areas include bionic robotics, intelligent perception & metrology, and related areas. He has published over 200 high-level academic papers, authored 3 monographies and 2 textbooks, held over 50 authorized invention patents as the first inventor, and developed 7 national standards. He has received the second prize from the Chinese Society of Automation and the second prize from the China Instrument and Control Society. He serves as the vice chairman of the Robotics Professional Committee of the China Association for Standardization, a member of the National Standards Committee Technical Committees TC591 and TC307, the vice secretary-general of the National Civil Aviation Metrology Technical Committee, and member of the Space Metrology Technical Committee.

Abstract

The process industry is a pillar and foundation of the national economy and a crucial support for my country's sustained economic growth. Its risk early warning and intelligent management and control are of great significance for my country's promotion of new industrialization and the implementation of the manufacturing power strategy. This forum focuses on multi-safety risk management and control, perception modeling, early warning decision-making, development of safety management rule sets and toolsets, and the development of industrial software support platforms in the process industry. It will bring together domestic and international experts to discuss the theories, methods, and key technologies of dynamic risk intelligent management and control in the process industry.

Chair: Prof. Youqing Wang Beijing University of Chemical Technology, China

Biography

Professor Youqing Wang is a professor at Beijing University of Chemical Technology, Dean of the School of Information Science and Technology, a National Distinguished Scientist, and an IET Fellow. He has published over 100 journal articles, led over 20 projects, and serves on the editorial boards of several international journals. He is the first scholar from mainland China to receive both the Best Paper Award from the *Journal of Process Control* and the ADCHEM Young Author Award. He has also received the First Prize of the Natural Science Award from the Chinese Association of Automation, the Second Prize of the Natural Science Award from the Ministry of Education, the Second Prize of the Beijing Natural Science Award, the Second Prize of the Shandong Provincial Natural Science Award, and the Fok Ying Tung Young Teacher Award.

Chair: Prof. Ningyun Lu Nanjing University of Aeronautics and Astronautics, China

Biography

Ningyun Lu is a professor at Nanjing University of Aeronautics and Astronautics, vice dean of the School of Automation, and a recipient of the Jiangsu Provincial High-Level Talent Training Program (“333 Project”). He has presided over more than 30 important projects/topics, including the National Natural Science Foundation of China and the National Key Research and Development Program. He has published 4 monographs and more than 160 papers, and has been granted more than 30 invention patents. He has won numerous awards, including the second prize of Jiangsu Provincial Teaching Achievement Award and the first prize of Jiangsu Provincial Science and Technology Award.

Abstract

With the continuous evolution of artificial intelligence technologies, the field of aircraft autonomous navigation and control has entered a new stage of development, garnering significant attention from both academia and industry. Simultaneously, the widespread deployment of modern aerospace technologies and UAV systems urgently demands more advanced autonomous navigation and control solutions. This imposes unprecedented and stringent requirements on theoretical reconstruction and technological innovation. Addressing how to leverage intelligent autonomous flight navigation and control technologies to significantly enhance the intelligence of aircraft, expand their application scopes and operational modes, and bolster aerospace technological progress and national aerospace security capabilities represents a key challenge with immense strategic potential that must be tackled. The Special Forum on "Intelligent Navigation and Flight Control Theory and Applications" aims to establish an open and interactive platform for academic exchange and intellectual engagement for experts and scholars in the fields of aerospace and intelligent control. Its ultimate goal is to accelerate the innovative development and practical implementation of intelligent technologies.
This forum brings together top-tier domestic experts and scholars to share frontier research findings and the latest technological breakthroughs. Participants will engage in in-depth discussions on prospective academic trends, with the aim of effectively broadening research perspectives and actively promoting the industrial application and transformation of advanced navigation and control achievements.

Chair: Prof. Bin Xu Northwestern Polytechnical University, China

Biography

Professor Bin Xu , Vice Dean of the School of Automation at Northwestern Polytechnical University, holds leadership roles including Chair of the Cognitive Computing and Systems Committee of the Chinese Association of Automation, Director of the Shaanxi Provincial General Aviation Systems Engineering Research Center, and Head of the Shaanxi Sanqin Team. His honors include the National Science Fund for Distinguished Young Scholars, Young Scientist Award from the Chinese Society of Aeronautics and Astronautics, and Shaanxi Youth Science and Technology Award. As primary contributor, he has received four major awards including the First Prize of Chinese Association of Automation and Second Prize of Shaanxi Provincial Science and Technology Award.
Research expertise spans navigation, guidance, and control, with leadership of over 30 projects including Key Program of National Natural Science Foundation of China and Civil Aircraft Special Project under the Ministry of Industry and Information Technology. The achievements have been applied to over 10 industrial units, including Aviation Industry Corporation of China and China Aerospace Science and Industry Corporation, and ground testing and flight verification have been conducted.
Editorial roles include Editor-in-Chief of SCI-indexed International Journal of Micro Air Vehicles, and editorial board positions for IEEE Transactions on Systems, Man, and Cybernetics: Systems, Journal of Intelligent & Robotic Systems, and Acta Automatica Sinica, plus Youth Editorial Board membership for Science China: Information Sciences. Recognized as Clarivate Highly Cited Researcher and Elsevier China Highly Cited Scholar. Service includes Chair of Organizing Committee for 2024 Conference on Control and Decision and General Chair for 2024-2025 Conference on Cognitive Computing and Systems.

Abstract

The wave of digital intelligence is systematically reconstructing the development paradigm of various industries. As a core field related to the national economy and human livelihood, medical healthcare is undergoing profound changes brought about by subversive technologies represented by artificial intelligence, big data, and cloud computing. The continuous accumulation of massive multimodal data, coupled with breakthroughs in both computing power and algorithms, is paving new pathways to overcome traditional challenges in healthcare, such as experience reliance, resource disparities, and inefficiency. By empowering clinical insight and medical decision-making, digital intelligence has become a crucial engine for advancing the quality and efficiency of healthcare services. This sub-forum aims to build an open and shared communication platform. It brings together experts and scholars across medicine, decision science, computer science, and data science, focusing on frontier issues in medical decision support, such as medical image analysis, clinical assistant diagnosis, smart hospital management, and medical resource allocation. Through in-depth dialogue and ideological collision, it is expected to explore a new paradigm for medical intelligent decision-making, characterized by greater accuracy, efficiency, and reliability, thereby providing intellectual support and methodological enlightenment for the innovative development of medical healthcare.

Chair: Prof. Zeshui Xu Sichuan University, China

Biography

Zeshui Xu received the Ph.D. degree in management science and engineering from Southeast University, Nanjing, China, in 2003. From October 2005 to December 2007, he was a Postdoctoral Researcher with School of Economics and Management, Tsinghua University, China. He was a Distinguished Young Scholar of the National Natural Science Foundation of China and the Chang Jiang Scholar of the Ministry of Education of China. He is currently a Chair Professor with Sichuan University, Chengdu. He has been elected as the member of AE, EASA, and IASCYS, the Distinguished Fellow of IETI, the Fellow of IEEE, IFSA, RSA, IET, ORS, BCS, IAAM, AAIA, AIIA, ACIS and VEBLEO. He is ranked 6th in Artificial Intelligence & Image Processing and 127th in career scientific impact among World’s top 100,000 Scientists in 2025 (released by Elsevier). He was awarded the 9th IETI Annual Scientific Award in 2024, published 23 monographs by Springer and contributed more than 1000 SCI/SSCI articles to professional journals. He is among the world’s top 1% most highly cited researchers with more than 110,000 citations, and his h-index is 162. He is currently the Associate Editor of IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, Information Sciences, Artificial Intelligence Review, Journal of the Operational Research, Fuzzy Optimization and Decision Making, etc. His current research interests include intelligent decision-making theory and methodology, optimization algorithms, information fusion, and big data analytics.

Abstract

With the development of science and technology, control of network systems composed of multiple autonomous agents has become a new research hotspot. In the research of networked system cooperative control, the complexity of the agent systems themselves, such as nonlinear unmodeled dynamics, external disturbances, and other uncertainties, as well as the complexity of network communication, such as attacks, information loss, and the ever-changing communication topology, present new challenges to existing control methods in terms of handling uncertainties, convergence speed, and control accuracy. This forum focuses on the high-performance control problems of complex network systems, exchanging new ideas, methods, and results in the broad field of nonlinear control, and fostering the development of new high-performance control theories and technologies.

Chair: Prof. Zhiliang Zhao North University of China , China

Biography

Zhiliang Zhao , Professor, PhD Supervisor, and Dean of the School of Electrical and Control Engineering at North University of China. He is also the Deputy Director of the High-Speed Flying Car Shanxi Provincial Laboratory. He holds several concurrent positions, including member of the Control Theory Professional Committee of the Chinese Association of Automation, Deputy Secretary-General of the ADRC Tecnical Committee of the Chinese Society of Command and Control, and editorial board member of journals such as Journal of Decision and Control and Systems Science and Mathematics. His primary research areas include nonlinear systems and control, ADRC, and finite-time control. He has published over 80 papers, and authored two monographs published by Wiley & Sons and Science Press. He has been the principal investigator for several projects, including those funded by the National Natural Science Foundation of China, the Key Project of the Natural Science Foundation of Shaanxi Province. He has received multiple prestigious awards, including the Second Prize in Natural Science from the Ministry of Education, the Second Prize in Natural Science from the Chinese Association of Automation, the Second Prize in Outstanding Natural Science Academic Papers from Shaanxi Province, and the First Prize in Scientific and Technological Achievements from Shaanxi Universities.