Special Sessions

Abstract

The integration of Industrial Large Models (ILMs) into chemical engineering presents a transformative paradigm for advancing safety production and quality control, motivated by the need to transcend the limitations of conventional methods in managing complex, nonlinear processes and volatile operating conditions. These models leverage vast, multi-modal datasets to enable predictive risk assessment, real-time anomaly detection, and cognitive process optimization. However, significant challenges impede their deployment, including data heterogeneity from disparate sources like Distributed Control Systems (DCS) and online analyzers, the critical need to embed physicochemical laws to ensure reliable and plausible model outputs, stringent real-time inference requirements for safety-critical decisions, and inherent vulnerabilities to adversarial attacks and a lack of interpretability in high-stakes environments. To overcome these barriers, this topic will systematically explore the potential techniques, such as physics-informed neural networks (PINNs) that harmonize data-driven learning with fundamental engineering principles, causal inference frameworks for robust root-cause analysis, federated learning architectures to preserve data privacy across production units, and high-fidelity dynamic digital twins for safe model training and validation. Future research should prioritize the development of domain-adapted fine-tuning strategies specifically for chemical processes, novel prompt-engineering frameworks that incorporate operational expertise, advanced explainable AI (XAI) for trustworthy decision-making in scenarios like emergency shutdowns, and the establishment of comprehensive regulatory standards for the safe and ethical application of ILMs in the chemical industry. This concerted effort is essential to unlock the full potential of industrial large models in creating more resilient, efficient, and inherently safer chemical processes.

Chair: Prof. Cuimei Bo Nanjing Tech University,China

Biography

Cuimei Bo is currently a Professor/Doctoral Supervisor, and serves as Vice Dean of the School of Electrical Engineering and Control Science at Nanjing Tech University, and as the academic leader of Control Science and Engineering. She concurrently holds the positions of Deputy Director of the Key Laboratory of Industrial Internet + Hazardous Chemical Safety Production Emergency Management (Ministry of Emergency Management), Director of the Jiangsu Green Intelligent Manufacturing Engineering Center, Chair of the Process Control Committee of Jiangsu Automation Society, and Deputy Director of the Intelligent Manufacturing Committee of China Chemical Society. Her research interests include the interdisciplinary innovation in dynamic modeling, advanced control, fault diagnosis, and fault-tolerant control for complex chemical process systems. She has presided over over 30 projects, including key projects of the National Key R&D Program and key projects of the National Natural Science Foundation of China, published more than 70 SCI papers, and authorized more than 60 invention patents. She has won more than 10 national and provincial/ministry-level awards, including thethe Second Prize of National Teaching Achievement Award, the Second Prize of Jiangsu Science and Technology Award, etc.

Chair: Prof. Wenli Du East China University of Science and Technology,China

Biography

Wenli Du is currently a Professor and Assistant to the President of East China University of Science and Technology, Dean of the Graduate School, Director of the National Center for Process Manufacturing Intelligence Regulation and Control Technology, and Deputy Director of the Key Laboratory of Energy-Chemical Process Intelligence Manufacturing of the Ministry of Education. She is also a standing director of the Chinese Association of Automation and the Chinese Association for Artificial Intelligence, among other professional affiliations. Her current research interests include control theory and applications, system modeling, advanced control, and process optimization. Prof. Du was a recipient of the National Science Fund for Distinguished Young Scholars. She was also a recipient of five State Science and Technology Progress Awards and 12 first prizes of provincial and ministerial-level Science and Technology Awards. She is an Associate Editor of seven international journals, including the Industrial & Engineering Chemistry Research, the Computers & Chemical Engineering, Complex & Intelligent Systems, and Frontiers in Chemical Engineering.

Chair: Prof. Jingsong Zhao Tsinghua University,China

Biography

Jingsong Zhao is currently a Professor and Ph.D. supervisor in the Department of Chemical Engineering at Tsinghua University. He formerly served as Head of the Department and is currently Director of the Institute of Process Systems Engineering and Deputy Director of the Beijing Key Laboratory of Industrial Big Data Systems and Applications. He is a member of the Hazardous Chemicals Safety Expert Committee of the State Council’s Work Safety Commission and a leading scholar in work safety in Beijing. He chairs the Engineering Ethics Education Committee of the Chemical Industry and Engineering Society of China (CIESC) and serves as Vice Chair of the CIESC Chemical Safety Committee. His research focuses on theories and methodologies for chemical process safety. By integrating fundamental principles of chemical engineering with big-data and artificial-intelligence technologies, he develops new theories, methods, and tools for chemical safety, advancing the intelligent evolution of the field. He is an Associate Editor of the Chinese Journal of Chemical Engineering (English edition) and Computers & Chemical Engineering, and a Thematic Editor of Process Safety and Environmental Protection. He has authored more than 120 peer-reviewed journal articles, published five monographs and one textbook, and filed or been granted over ten invention patents. Has won the First Prize and the Second Prize for Scientific and Technological Progress of the China Petroleum and Chemical Industry Federation, etc.

Abstract

In order to meet the increasing demands for safety, reliability, and production efficiency, enterprises in the process industry continuously introduce advanced automation and intelligent technologies to ensure stable and efficient operation of production processes. As market competition intensifies, the operational safety of industrial equipment and the long-term efficient operation of production processes have become particularly crucial. Any inefficient operation, downtime, or even fault can result in significant economic losses. Technologies driven by knowledge and data have shown great potential in improving the operational performance, fault diagnosis, and intelligent maintenance of process industries. The use of big data analytics and artificial intelligence algorithms provides strong support for accurate performance evaluation, equipment fault diagnosis, and effective maintenance strategies. This topic will systematically explore the current applications, technological advancements, achievements, challenges, and future development directions of the technologies driven by knowledge and data in the fields of process industry operating performance assessment, fault diagnosis, and intelligent maintenance, based on industrial process intelligent monitoring.

Chair: Prof. Yuqing Chang Northeastern University,China

Biography

Yuqing Chang is currently the Professor and Doctoral Supervisor at the School of Information Science and Engineering, Northeastern University, and the Director of the Department of Industrial Intelligence and Automation. She is also a Teaching Master of Liaoning Province.
She has led nearly 10 projects, including sub-projects of the National Natural Science Foundation of China (NSFC) Key Program, General Program, and sub-projects under the Ministry of Science and Technology's 863 Program, as well as over 20 corporate R&D projects. She has published more than 100 papers in domestic and international journals and conferences, including over 35 SCI-indexed papers, and authored several textbooks and monographs. She has also applied for more than 10 national invention patents. Professor Chang has received nearly 10 awards, including the Scientific and Technological Progress Award from the Chinese Association of Automation, the Outstanding Scientific Research Achievement Award in Natural Sciences from Higher Education Institutions, and the China Nonferrous Metals Industry Science and Technology Award. As a project leader, she has undertaken over 30 major projects, including national key R&D programs, major NSFC projects, major sub-projects of the 863 Program, and significant corporate projects. Her main research interests include process modeling, monitoring, quality prediction, operating performance assessment, fault diagnosis and performance maintenance, and process optimization in the process industry.

Chair: Prof. Chunhui Zhao Zhejiang University,China

Biography

Chunhui Zhao is currently Qiushi Distinguished Professor for Zhejiang University. She received Ph.D. degree from Northeastern University, China, in 2009. From 2009 to 2012, she was a Postdoctoral Fellow with the Hong Kong University of Science and Technology and the University of California, Santa Barbara, Los Angeles, CA, USA. From 2012 to 2014, she was a distinguished researcher with Zhejiang University and since Dec. 2014, she has been a Professor with the College of Control Science and Engineering, Zhejiang University, Hangzhou, China.
Her research interests include statistical machine learning and data mining for industrial application. She has authored or coauthored more than 220 papers in peer-reviewed international journals. She has published 3 monographs and two national textbooks. She authorized more than 60 invention patents. She is principal investigator of a Distinguished Young Scholar Program supported by the Natural Science Foundation of China. She has hosted more than 20 scientific research projects, including the NSFC funds, National key R&D project, provincial projects and corporate cooperation projects. She has received the Ministry of Education Natural Science Award, the First Prize of Natural Science of Chinese Association of Automation, and other provincial and ministerial awards. She also received more than ten academic awards, including Chinese Young Female Scientist Award, CAA Fellow and the First Young Women Scientists Award of CAA, etc. She has served AE of three International Journals, including Journal of Process Control, Control Engineering Practice and Neurocomputing, and three domestic journals, including Control and Decision, etc.

Chair: Assoc. Prof. Shuai Tan East China University of Science and Technology,China

Biography

Shuai Tan is currently the Associate Professor at East China University of Science and Technology, Deputy Dean of the School of Information Science and Engineering.
Her research areas include fault monitoring and operational status evaluation for complex processes and large equipment. She has been responsible for over 20 research projects, including sub-project of the National Key R&D Program of China, the National Natural Science Foundation of China (NSFC) Program, the Shanghai Natural Science Foundation Program etc. She has received the Second Prize of the Shanghai Natural Science Award, the Second Prize of the Liaoning Provincial Natural Science Academic Achievement Award, the First Prize and the Second Prize of the Shanghai Teaching Achievement Award. She has published one monograph, more than 90 papers, and more than 10 patents. Shuai Tan currently serves as member of CAA Fault Detection, Supervision, and Safety for Technical Processes Committee, and as member of CAA Intelligent Control and Systems Committee.

Abstract

With the development of science and technology as well as the deep integration of information and physical systems, the control systems in practical industries have become increasingly complex, thus making it difficult to establish their accurate mathematical models. In this context, the offline/online data-driven control theory has been developed rapidly. The data-driven adaptive and learning methods can describe the complex systems by establishing the dynamical relationships of the I/O data, mine the operating modes and periodic repetitive features of the systems. Then, these modes and features are used to adjust control input behavior to achieve a good control of complex systems. Therefore, data-driven adaptive and learning methods have attracted widespread attention in recent years. On the other hand, with the implementation of the national strategy for artificial intelligence (AI), how to introduce AI algorithms and technologies into data-driven adaptive and learning control has become an urgent problem to make system have stronger learning ability and adaptability for the complex control tasks under uncertain scenarios.

Chair: Prof. Ronghu Chi Foshan University,China

Biography

Ronghu Chi ,Full Professor of Foshan University, Senior member of Chinese Association of Automation (CAA). He received the Ph.D. degree in systems engineering from Beijing Jiaotong University, Beijing China, in 2007. He was a Visiting Scholar with Nanyang Technological University, Singapore and a Visiting Professor with University of Alberta, Edmonton, AB, Canada. He also serves as the TPC Chair of IEEE Data Driven Control and Learning Systems Conference (DDCLS), Deputy Director of Society of Data Driven Control, Learning and Optimization of Chinese Association of Automation (CAA), senior member of CAA, member of IEEE, member of Process Control Professional Committee, CAA. He was awarded the “Taishan scholarship” in 2016. He hosted over 20 scientific research projects, including the National Natural Science Foundation of China, Shandong Provincial Key R&D Program, and Qingdao Major Independent Innovation Project. He has published 2 books, more than 100 refereed journal articles. He has won 8 scientific research awards including the second prize of CAA natural science award and he has authorized more than 10 invention patents. His research interests include: data-driven control, intelligent learning control, etc.

Chair: Prof. Dong Shen Renmin University of China,China

Biography

Dr. Dong Shen received the B.S. degree in mathematics from School of Mathematics, Shandong University, Jinan, China, in 2005, and the Ph.D. degree in mathematics from the Academy of Mathematics and System Science, Chinese Academy of Sciences (CAS), Beijing, China, in 2010. From 2010 to 2012, he was with the Institute of Automation, CAS. From 2012 to 2019, he was with the Beijing University of Chemical Technology, Beijing, China. He was a Visiting Scholar at National University of Singapore, Singapore, and RMIT University, Australia. He is a Wu Yuzhang Distinguished Professor with the School of Mathematics, Renmin University of China, Beijing, China. His current research interests include iterative learning control, stochastic optimization, and distributed artificial intelligence. He has published 6 monographs and more than 50 papers in IEEE Transactions, JAS, and Automatica.

Chair: Prof. Xuhui Bu Henan Polytechnic University,China

Biography

Xuhui Bu is a Full professor at Henan Polytechnic University and Senior member of Chinese Association of Automation (CAA). He received the Ph.D. degree in control theory and application from Beijing Jiaotong University, Beijing China, in 2007. He has authored over 90 peer-reviewed journal articles and over 40 articles in prestigious conference proceedings. His research interests include data-driven control, iterative learning control, traffic control and networked system control. He has led four National Natural Science Foundation projects and over 10 provincial-level and industry collaboration projects. As the first completer, he received one Second Prize for Henan Provincial Science and Technology Progress and one Second Prize for Henan Provincial Natural Science Awards.

Abstract

Low-altitude intelligent transportation system (LAITS) has emerged as a promising research area. Connected and automated vehicles (CAVs), on roads, waterways and in the air at low altitudes, have the ability of gathering and sharing vehicle states and environment information with neighboring vehicles of various types, the infrastructures and the operation control center. With the advent and increasing maturity of V2X, CAVs are believed to be an important technology to deliver greater safety and mobility benefits to the next generation intelligent transportation systems (ITSs). On the other hand, artificial intelligence (AI) and big data (BD) technologies provide us with powerful tools and more possibilities to develop novel smarter ITSs technologies. This session mainly focuses on the current development, new progress, the results (theory, experiment), and challenges of related AI and BD technologies in the fields of CAVs and LAITSs from both theoretical and practical perspectives.

Chair: Prof. Ge Guo Northeastern University,China

Biography

Ge Guo , Professor in Northeastern University (NEU), China; He was dean of School of Control Engineering, NEU Qinhuangdao Campus. He received the B.S. degree and the PhD degree from Northeastern University, Shenyang, China, in 1994 and 1998, respectively. He has published over 200 papers on top international journals within his areas of interest, which include operation optimization of intelligent transportation systems, cyber-physical systems, etc. He is one of the Elsivier Highly Cited Researchers and on the Stanford/Elsevier Top 2% Scientists List.
Dr. Guo is a Senior Editor of IEEE Transactions on Intelligent Transportation Systems and an Associate Editor of a variety of international journals and Chinese Journals, including IEEE Transactions on Vehicular Technology, IEEE Transactions on Intelligent Vehicles, IEEE Intelligent Transportation Systems Magazine, Information Sciences, ACTA Automatica Sinica, China Journal of Highway and Transport and Journal of Control and Decision, etc. He won the CAA Young Scientist Award, the First Prize of Natural Science Award of Hebei Province, the First Prize of Science and Technology Progress Award of Gansu Province, the First Prize of Science and Technology Progress Award of Liaoning Province, and the Second Prize of Natural Science Award of Gansu Province.

Abstract

Recent years have witnessed a rapid development of advanced technologies, low-cost devices and artificial intelligence (AI), distributed control and intelligent algorithms, including learning/data-based control, optimization, game theory, have become hot topics in both theoretical research and industrial applications across the world, such as robotics, autonomous vehicles, unmanned aerial vehicles and artificial intelligence, which, in turn, have thus far motivated the rapid development of a wide spectrum of centralized/decentralized algorithms. They also have far-reaching impact on social prosperity and national development. The goal of this special session is to bring together the researchers and practitioners to discuss recent advancements on the related fields.

Chair:Prof. Xiuxian Li Tongji University,China

Biography

Xiuxian Li is a professor with National Key Laboratory of Intelligent Autonomous Systems, College of Electronic and Information Engineering, and Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China. He received the Ph.D. degree in mechanical engineering from HKU, Hong Kong, in 2016. He is the recipient of IEEE ICCA 2025 and an associate editor of Journal of Control and Decision and IEEE Open Journal of Control Systems. His research interests include distributed control and optimization, game theory, as well as applications to autonomous vehicles. He has published more than 60 SCI journal papers, and is a senior member of CAA, CICC and IEEE.

Abstract

With the proposal and implementation of the national major strategy of "carbon peaking and carbon neutralization", renewable energy represented by wind power and photovoltaic can be vigorously developed and utilized, which will profoundly change the pattern of China's power and energy industry. Artificial intelligence (AI) technology represented by big data, cloud computing, Internet of things, digital twin, intelligent computing, deep learning and intensive learning is an important driving force for the development of Smart Grid and Energy Internet. It will promote the deep integration of power, energy, information, transportation and other fields, enable the production, transmission and utilization of power and energy, support the effective consumption of large-scale new energy, and help China achieve the dual carbon strategic goal. On the other hand, with the impact of climate change and human activities, China's power and energy demand continues to grow, which will put forward higher requirements on the planning, operation, control and information processing technology of Smart Grid and Energy Internet. It is urgent to establish a high-intelligent control and decision-making platform based on AI technology. From the perspective of theory and practice, this topic will exchange and discuss AI and its research status, progress, achievements and existing challenges in Smart Grid and Energy Internet.

Chair:Prof. Yuanzheng Li Huazhong University of Science and Technology, China

Biography

Yuanzheng Li is an Professor in School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Recipient of the National Excellent Youth Funding, a joint doctor of the University of Liverpool in UK and South China University of Technology, and a Senior Member of IEEE. His main research fields are AI enabled smart grid and energy internet. He has published two Springer monographs as the first author, and the research were published as the first author in the journal of Nature Reviews Electrical Engineering and Proceedings of the IEEE. At the same time, more than 40 international authoritative journal papers such as IEEE Transactions, and more than 30 first author/corresponding papers have been published. Among them, 9 papers have been awarded journal features/ESI hot topics/highly cited papers. He served as the editorial board member of five authoritative domestic and foreign publications, including IEEE Transactions and IET, and co-chairman of the branch of China Control and Decision Making Conference (CCDC). He won the second prize of Tianjin Science and Technology Progress Award, and Tencent Patent Project Award in 2022 as the principle investigator.

Chair:Prof. Zhigang Zeng Huazhong University of Science and Technology, China

Biography

Zeng Zhigang , IEEE Fellow, Dean of the School of Artificial Intelligence and Automation at Huazhong University of Science and Technology, Director of the Key Laboratory of Image Information Processing and Intelligent Control of the Ministry of Education. Obtained a Ph.D. in System Analysis and Integration from Huazhong University of Science and Technology in June 2003. Conducted postdoctoral research at the Chinese University of Hong Kong and the University of Science and Technology of China. Served as an editorial board member for IEEE Transactions on Neural Networks, IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, Cognitive Computation, Neural Networks, Applied Soft Computing, Acta Automatica Sinica, Control Engineering, Systems Engineering and Electronics, and Control Theory and Applications. Received awards such as the Ministry of Education Natural Science Award (First Prize), Hubei Province Natural Science Award (First Prize), Hubei Province Science and Technology Progress Award (First Prize), and the National Science and Technology Progress Award (Second Prize).

Abstract

Smart manufacturing is an important way to integrate the manufacturing industry with the new generation of information technologies such as artificial intelligence, cloud computing, the Internet of things, and big data, so as to realize the digital transformation, upgrading and innovative development of the manufacturing industry.

The purpose of this session is to bring researchers engaging in intelligence manufacturing together to cooperate and communicate with each other. Experts and scholars, graduate students in the areas related to the intelligent manufacturing are warmly invited to submit their original research results. The articles cover the following topics: intelligent analysis and decision making; logistics and supply chains; production planning and scheduling; intelligent manufacturing knowledge management; manufacturing service management; industrial big data and its application in intelligent manufacturing; industrial robots; cyber physical system and intelligent factory.

Chair: Prof. Shixin Liu Northeastern University,China

Biography

Shixin Liu is a professor at the School of Information Science and Engineering, Northeastern University, and Dean of the School of Control Engineering at Northeastern University at Qinhuangdao. He has been selected into the New Century Excellent Talents Program of the Ministry of Education, and recognized as a Leading Talent in Scientific and Technological Innovation of Liaoning Province. He concurrently serves as a Senior Member of IEEE, Deputy Director of the Industrial Software Standardization Working Group of the China Iron and Steel Industry Association, Deputy Director of the Management Systems Engineering Professional Committee of the Chinese Society of Management Science and Engineering, and an editorial board member of journals Control and Decision and Metallurgical Automation. Professor Liu has long been engaged in theoretical, methodological, and technological research in intelligent manufacturing, machine learning, and intelligent optimization methods. He has presided over more than 30 research projects, including those funded by the National Key Research and Development Program, General Program of the National Natural Science Foundation of China, key projects of the Ministry of Industry and Information Technology, as well as major enterprise research projects. He has published over 200 academic papers, applied for 18 invention patents, formulated 3 group standards, and registered 12 software copyrights.

Chair: Prof. Jing Bi Beijing University of Technology,China

Biography

Jing Bi is a Professor and Ph.D. supervisor at Beijing University of Technology, and Deputy Director of the AI Sub-Committee of the Zhongguancun General Science and Technology Alliance. Her research focuses on intelligent sensing and control of complex systems. She has led multiple national and provincial research projects, including grants from the National Natural Science Foundation of China, major programs of the Ministry of Science and Technology, and key research initiatives of Beijing Municipality. She has published over 200 papers in international journals and conferences, including more than 80 JCR Q1 SCI papers as first or corresponding author, with more than 5,400 Google Scholar citations. She holds over 50 U.S. and Chinese invention patents and software copyrights, and has authored four monographs. She has been listed among the “World’s Top 2% Scientists” in AI and image processing. She has received significant awards such as the First Prize of the Science and Technology Progress Award of the Chinese Association for System Simulation, the Second Prize of the Science and Technology Progress Award from the Chinese Association of Automation and the Chinese Society for Environmental Sciences, and the Silver Medal at the International Exhibition of Inventions Geneva. She serves as Associate Editor of IEEE Transactions on Systems, Man and Cybernetics: Systems and IEEE Transactions on Industrial Informatics, and holds editorial roles in several other journals. She is a Senior Member of IEEE and CAA, and an active member of multiple national professional committees in AI, automation, and intelligent systems.

Abstract

Fractional calculus and fractional-order systems are rapid developing topics in science and engineering of today. For certain systems, the integer-order modeling techniques may not yield accurate descriptions to the systems behaviors, especially to the systems with memories. Fractional calculus brings in a new way in system modeling, and successful cases can be found in control theory, mathematics, mechanics, biology, chemistry, and signal and image processing. The research areas in the special session include fundamental theory in fractional calculus, numerical algorithms and implementations in fractional calculus, stability and qualitative analysis of fractional-order systems, strategies and algorithms in fractional-order control systems, modeling, analysis, simulation and design in fractional-order controls, modeling, identification and applications in special materials, fractional derivative modeling of physical processes in complex media, fractional calculus applications in signal and image processing, fractional calculus applications in science and engineering.

Chair: Prof. Junguo Lu Shanghai Jiao Tong University,China

Biography

Junguo Lu , Professor, Department of automation, School of electronic information and electrical engineering, Shanghai Jiao Tong University. Main research interests: fractional-order control system, intelligent robot and its system, unmanned driving, etc.

Chair: Prof. Dingyu Xue Northeastern University,China

Biography

Dingyu Xue received his doctorate from Sussex University, England in 1992. He is now a professor at Northeastern University, China. He started the research work on fractional calculus and control since earlier 2000s, and had contributions include high-precision algorithms, simulation schemes for fractional-order differential equations of any complexity, stability of irrational systems and fractional-order controller design. His recent monograph “Fractional-order Control Systems – Fundamentals and Numerical Implementations” (Berlin: De Gruyter, 2017) bridges the gap between the theoretical work and numerical implementation, such that any research may try to introduced fractional calculus into his own fields and compare the results. His MATLAB FOTF Toolbox is one of the four major toolboxes in fractional-order control community worldwide, and it is now the only one for irrational systems modeling, analysis and design.

Abstract

This topic has been held for the twelfth consecutive year, the purpose of which is to gather colleagues engaged in automation and intelligence in the field of architecture for cooperation and exchange. This forum truly reflects the characteristics of paper reading and face-to-face discussion, and reserves time for all participants to actively ask questions and consult. The establishment of small peer offline communication, online group building and other academic exchanges based on conference exchange, rather than the convenience can be endowed by other forms academic exchanges. Warmly welcome experts, scholars and graduate students in the field of control and management of smart cities (architecture) to submit their papers.

Chair: Prof. Hongyan Ma Beijing University of Civil Engineering and Architecture, China

Biography

Hongyan Ma ，Professor, Deputy Dean of School of Intelligence Science and Technology, Beijing University of Civil Engineering and Architecture. She received the Ph.D. degree from Tsinghua University, Beijing, China. From 2015 to 2016, she was an Academic Visitor with the University of Nottingham, U.K. She is selected in Talents of the Organization Department of Beijing Municipal Committee of CPC, Young and middle-aged talents of Beijing Municipal Education Commission. She serves as a senior member of SAC/TC205 and an expert of Green Building and Intelligent Building Branch of China Construction Industry Association etc. She is the leader of automatic control principle which is national first-class course.

Her main research interests include high performance control of PMSM, energy-saving control of building equipment and energy storage technology. She has completed more than 20 scientific research and engineering projects. She has published more than 70 papers, edited and written 10 books.

Chair: Prof. Yahui Wang Beijing University of Civil Engineering and Architecture, China

Biography

Yahui Wang , Professor, School of Intelligence Science and Technology, Beijing University of Civil Engineering and Architecture, Deputy Director of the Robot Engineering Committee of the New Engineering Alliance of the Ministry of Education，Member of Construction Robot Professional Committee of Chinese Society of Automation, Member of the Construction Robot Committee of China Engineering Construction Standardization Association, Member of the Professional Evaluation Committee of senior professional titles in Ministry of Housing and Urban-Rural Development，Special consultant of intelligent gas Network Committee of China City Gas Association.

His research interests include: robotics，intelligent gas，project management and emergency management in municipal engineering. Completed more than 20 scientific research and engineering projects, and won many awards. He has edited more than 10 books, published more than 100 papers, and supervised more than 100 graduate students.

Abstract

Process industry is the pillar industry of national economy, and its automation level will directly affect the international competitiveness of enterprises and the industrial sectors. With the integration of industrialization and informatization, process industry is developing towards the intelligent production, following the developments of Industry 4.0 and Intelligent Manufacturing 2025. In corresponding to industrial big data, data-driven techniques can effectively support intelligent modeling, optimization, control and decision-making of process industrial processes. For ensuring safer, more efficient, and greener production operations, process optimization and decision-making should integrate with emerging intelligent methodologies. The main topics covered by this session include data-driven intelligent modeling of industrial processes, accurate recognition of operating status, online tracking of abnormal and fault factors, self-healing control of abnormal working conditions, optimization of production and operation, safe operation decision-making, intelligent control and so on, as well as other emerging technologies related to industrial processes, including virtual simulation, intelligent recognition and advanced computing, etc.

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

Biography

Prof. Jing Na is currently a Professor with the Faculty of Electrical & Mechanical Engineering at Kunming University of Science & Technology. He received the B.S. and Ph.D. degrees from the School of Automation, Beijing Institute of Technology, China, in 2004 and 2010, respectively. From January 2011 to December 2012, he was a Monaco/ITER Postdoctoral Fellow with the ITER Organization, France. He is currently the director of the municipal Key Laboratory of Intelligent Control and Application.

His current research interests include parameter estimation, adaptive control, nonlinear control and application. He has published 2 monograph in Elsevier, and more than 100 refereed papers, and authorized more than 10 invention patents. He is currently the Associate Editor of IEEE TIE and Neurocomputing, and has served as the General Co-chair of ICMIC 2017, Organization Co-chair of CCDC 2021. Dr Na has also been awarded the Best Application Paper Award of the 3rd IFAC International Conference on Intelligent Control and Automation Science (IFAC ICONS 2013), the “Hsue-shen Tsien” Paper Award, Second Prize of Natural Science of Yunnan Province, and been the winner of the China Youth May Fourth Medal, National Excellent Teacher.

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

Artificial intelligence has become a strategic technology, leading the new sci-tech revolution and industrial transformation. This trend has a significant impact on the talent cultivation of control relevant disciplines. For thoroughly implementing the spirit of Strengthening Education Strategy, National Education Conference and Postgraduates Education Conference, accelerating education modernization, coping with new challenges emanating from the new developing relevant programs of control disciplines in higher education, the special session: Reform and Innovation on Intelligent Control Discipline Education, is established to focus on the central issues of professional talent training quality and education & teaching reform. The purpose is to exchange the latest research achievement and progress in the construction and reform of automation relevant programs in undergraduate and postgraduate education. We warmly welcome active contributions from experts and scholars in relevant fields.

Chair:Prof. Feng Pan Northeastern University, China

Biography

Prof.Feng Pan ,Northeastern University, Shenyang, China. Director of China Simulation Federation and Secretary-General of Liaoning Association for Artificial Intelligence.He has devoted himself to the teaching reform & construction for many years. As the main member, he has won more than ten important teaching awards, such as the second prize of National Teaching Achievement, the first prize of Liaoning Provincial Teaching Achievement, and the first prize of Higher Education Teaching Achievement of Chinese Association of Automation. He has undertaken ten provincial and ministerial teaching research and reform projects. He teaches one national excellent course and two of the national first-class undergraduate courses. He has published more than 10 teaching reform papers in teaching journals and conferences.

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

Smart energy is an environmentally friendly energy system which has functions of learning, adaptation and self-organization to meet the requirements of system security, economy, cleanliness and high efficiency. Smart energy with advanced new energy control can not only alleviate the energy crisis and pressure, adapt to the needs of human development, but also promote the progress of civilization and accelerate the industrial transformation. Therefore, smart energy should be the focus of research now and in the future.

Smart energy, especially the new energy control, still has great potentials for making further progress. The performance of smart energy is limited by computational complexity, heterogeneous data, multiple time scale and so on. The high requirements such as analysis of complex operating conditions, real-time optimization of hybrid energy motivate smart energy to improve control method or consider combining with diversified advanced method. Further research is essential to advance the development of smart energy and sustainable energy control.

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.

Chair: Prof. Xuguang Hu Northeastern University, China

Biography

Xuguang Hu is an Associate Professor and Ph.D. supervisor at Northeastern University. His research focuses on intelligent modeling, state analysis, and operational control of energy systems driven by hybrid digital-physical mechanisms. He has published more than 20 papers in journals such as the IEEE Transactions series, with several recognized as ESI Highly Cited Papers. He holds over 10 authorized patents and has authored a monograph included in China’s “14th Five-Year Plan” National Key Book Publishing Program.

As a key contributor, he has received multiple major awards, including the Second Prize of the Liaoning Provincial Science and Technology Progress Award, the First Prize of the Natural Science Award of the Chinese Association of Automation, and the First Prize of the Science and Technology Progress Award of the Chinese Association of Automation. He currently serves as the Secretary of the Energy Internet Technical Committee of the Chinese Association of Automation and as an Editorial Board Member for special issues of international and domestic journals such as IET Renewable Power Generation.

Abstract

With the rapid advancement of autonomous navigation technologies, unmanned systems are evolving into more intelligent, efficient, and adaptive systems, suitable for a wide range of complex applications. Researchers are increasingly leveraging smart technologies to address real-world challenges characterized by high uncertainty and variability, such as environmental awareness, mission planning, and real-time decision-making. The integration of these smart technologies with unmanned systems offers numerous advantages, including adaptive learning, optimized control strategies, and enhanced autonomy. This has spurred significant interest in research areas such as advanced sensor fusion, robust control algorithms, real-time data analysis, and multi-agent cooperation strategies. The goal of smart technologies is to enhance the functionality and accuracy of unmanned systems, endowing them with adaptive and intelligent decision-making capabilities, and facilitating their applications.

Chair:Prof. Zhengrong Xiang Nanjing University of Science and Technology, China

Biography

Zhengrong Xiang , Professor and PhD Supervisor at Nanjing University of Science and Technology. He currently serves as a member of several academic societies, including the Chinese Association of Automation and the Chinese Association of Artificial Intelligence, and has been awarded the Second-Class Prize for Technological Advancement at the provincial and ministerial levels. He has led multiple national and provincial-level natural science fund projects, key research and development programs, and enterprise-commissioned projects. He has published over one hundred academic papers in domestic and international journals and conferences, and holds more than ten authorized national invention patents. Several of his papers have been selected as ESI Highly Cited Papers, among the "Top 100 Most Influential International Academic Papers in China," and as Excellent Academic Papers in Jiangsu Province's Natural Science category. His primary research interests include multi-agent systems, unmanned systems, nonlinear systems, and the control theory and applications of switched systems.

Chair: Prof. Yueying Wang Tongji University, China

Biography

Yueying Wang , Researcher/PhD Supervisor, School of Computer Science and Technology, Tongji University. He mainly engages in research on intelligent perception, control, and decision-making for unmanned marine systems. In recent years, he has published more than 40 papers as the first/corresponding author in authoritative domestic and international journals/conferences such as IEEE/ACM Transactions and AAAI. He holds over 20 authorized Chinese/American invention patents and has been listed in the "Global Highly Cited Researchers" and "Highly Cited Chinese Researchers" rankings. He presides over projects including the Young Scientists Fund (Class B) of the National Natural Science Foundation of China, the Regional Joint Key Project, and research topics of the National Key R&D Program. He also participates as a core member in the Class A Innovation Group Project of the National Natural Science Foundation of China. He serves as an editorial board member for 8 international SCI journals including IEEE Transactions on Cybernetics (IEEE TCYB) and IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS); a member/co-member of the Professional Committees on Robotics, Intelligent Robotics, and Control Theory of the Chinese Association of Automation (CAA); an executive member of the Technical Committees on Computer Vision and Intelligent Robotics of the China Computer Federation (CCF); an executive member of the Youth Working Committee of the Chinese Society of Image and Graphics (CSIG); and a director of the Shanghai Association of Automation. He has won one Second Prize of the Ministry of Education Natural Science Award as the first completer, and one First Prize of the Guangxi Natural Science Award as the second completer.

Chair: Assoc. Prof. Weixiang Zhou Shanghai Maritime University, China

Biography

Weixiang Zhou is an Associate Professor and Master Supervisor at Shanghai Maritime University. He was selected for the Shanghai Rising Star Talent Program. He is a principal investigator of the National Natural Science Foundation. His research interests include intelligent control and decision-making of unmanned systems, multi-agent systems, and marine unmanned equipment.

Abstract

Marine unmanned systems refer to a general term for various types of air/surface/underwater unmanned platforms. They have the autonomous navigation capabilities, which can accomplish different tasks such as information collection, fixed/mobile target detection, identification, localization, tracking and encirclement. Typically, these platforms include unmanned aerial vehicles (UAVs), unmanned surface vessels (USVs), autonomous underwater vehicles (AUVs), remotely-operated vehicles (ROVs), and so on. During the procedures of understanding and exploring the ocean, marine unmanned systems have become an important safeguard for seizing the commanding heights of ocean technology due to their high maneuverability, strong adaptability and low maintenance costs. As the key technologies of marine unmanned systems, the swarm perception and cooperation control have shown great potential in marine application scenarios, which enable the transition from individual intelligence to collective intelligence. Meanwhile, they are crucial for enhancing the response capabilities of unmanned platforms in complex marine environments. From the theoretical and practical perspectives, this topic discusses and exchanges the research status, progress, achievements, and challenges in the perception and cooperation control of marine unmanned systems.

Chair: Prof. Jing Yan Yanshan University,China

Biography

Prof Jing Yan is a Professor and Doctoral Supervisor with Yanshan University. His research interests cover in the localization, networking and cooperation control for underwater network systems. He received the Excellent Youth Project for NSF of China, the Distinguished Youth Project for NSF of Hebei Province, the Excellent Doctoral Dissertation of Hebei Province, and the Second Prize of Natural Science of Hebei Province. He was also honored as the young scientists of maritime power and Yanzhao. Currently, he is a Senior Member of IEEE and the Chinese Society of Automation. He serves as the Associate/Young Editors of some journals, e.g., IEEE Transactions on Intelligent Transportation Systems, Ocean Engineering, IEEE/CAA Journal of Automatica Sinica, IEEE Systems Journal, IET Control Theory & Applications, Control Theory and Applications, Control and Decision, Robot, and Underwater Unmanned Systems. In recent years, he has authored over 80 referred international journal and conference papers, such as IEEE TAC and IEEE JOE. Meanwhile, he is also the inventor of seventeen patents. In addition, he guided students to win the first prize in the IEEE/OES Chinese Ocean Acoustics H2O Competition, the runner up in the World University Underwater Robot Competition, the Most Popular Work Award at the Chinese Control and Decision Conference, the Best Student Paper Award and the IEEE CYBER Conference, and the Best Paper Award and the CAIBDA Conference.

Chair: Prof. Xinping Guan Shanghai Jiao Tong University,China

Biography

Xinping Guan is a Chair Professor and PhD supervisor at Shanghai Jiao Tong University. He is a recipient of the National Outstanding Youth honored by the National Natural Science Foundation of China (NSFC), the Changjiang Scholar of the Ministry of Education of China, the State-Level Scholar of the New Century Bai Qianwan Talent Program of China, and the State Council Government Special Allowance. He is an IEEE Fellow, and serves on the boards of the Chinese Association of Automation and the Chinese Association for Artificial Intelligence. Guan Xinping leads an innovation group funded by the NSFC, serves as Chief Scientist for a national major scientific instrument project, and is responsible for the development of a certain naval equipment. He is an editorial board member for several journals and has received numerous awards, including two Second Prizes of the National Natural Science Award of China, the IEEE TCCPS Industrial Technical Excellence Award, and two First Prizes of the Ministry of Education Natural Science Award. Guan Xinping has authored five monographs, published over 300 high-level papers in journals such as IEEE Transactions and Automatica, with more than 20,000 citations on Google Scholar. He holds over 100 authorized patents in China and the United States, with multiple technology transfer achievements.

Chair: Yichen Li Shanghai Jiao Tong University,China

Biography

Yichen Li is an Assistant Professor in the School of Automation and Intelligent Sensing at Shanghai Jiao Tong University. He has been selected for the Young Elite Scientist Sponsorship Program by the China Association for Science and Technology and the Shanghai "Super Postdoctoral" Incentive Program. He has received awards including the First Prize of Science and Technology Progress Award (Technological Invention Category) from the Chinese Association of Command and Control, the "Top Ten Scientific and Technological Advances" award from Shanghai Jiao Tong University, the Outstanding Doctoral Dissertation Award from the Chinese Association of Command and Control, and the First Prize of Technological Invention from the Shanghai Association of Automation. Based on marine unmanned systems, his research primarily involves underwater target tracking, underwater positioning, and multi-source fusion. He has published 37 papers in international journals and conferences, including IEEE TII, IEEE/CAA JAS, IEEE JOE, IEEE TCYB, etc., with 21 of these as first author or corresponding author. Additionally, he has applied for 20 patents, with 6 already granted, and registered 2 software copyrights.

Abstract

The International Energy Agency (IEA) undertook efforts to improve understanding of the growing interlinkages between energy and digitalization since October 2017. Nowadays, there has been enormously growing energy big data everyday, and thanks to the fast development of modern information communication technologies and digital twins, the energy system digitalization emerges.
Using the digital technology, the energy big data and energy digitalization can orderly manage the energy flow to form a cleaner, more efficient, and more economic energy system, while maintaining the secure and stable operation, effective productivity, and sustainability.
The main areas of this special session include the framework, mechanism, models, planning, operation, optimization, stability, control, analytics, economics, and fault diagnosis of energy big data and energy system digitalization. Several other cutting-edge technologies, including digital twins, edge computing, distributed computing, and advanced sensors, which are related to energy systems are also included.

Chair: Prof. Dongsheng Yang Northeastern University,China

Biography

Prof Dongsheng Yang ，is the deputy dean of College of Information Science and Engineering at Northeastern University and recognized as National High-Level Talent. His research interests mainly include energy system analysis based on complex network theory, artificial intelligent & power distribution technology, big data & digital twins, and fault diagnosis. He is selected in New Century Talent Supporting Project by Ministry of Education, Chair Professor of Liaoning Revitalization Talents Program, and Liaoning Bai-Qian-Wan Talents Program (Hundred-Talent Level).

Prof. Yang co-authored two books and more than 70 papers. He holds more than 80 patents in China and USA. He had undertaken about 30 research projects, sponsored by National Natural Science Foundation of China, State Grid Corporation of China, and so forth. He won the Second Prize of the National Science and Technology Progress Award, and the Gold Award of Geneva International Exhibition of Inventions. He is currently a standing member of Energy Internet Equipment and Technology Association of China Machinery Industry Federation and the Secretary of IEEE PES China Transformer Committee. He is currently a senior member of IEEE and Fellow of IET.

Chair: Prof. QinMin Yang Zhejiang University,China

Biography

Qinmin Yang received the Ph.D. degree in electrical engineering from University of Missouri-Rolla, Rolla, MO, USA, in 2007. Afterwards, he was an Advanced System Engineer with Caterpillar, Inc. From 2009 to 2010, he was a Postdoctoral Research Associate with the University of Connecticut, Storrs, CT, USA. Since 2010, he has been with the State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China, where he is currently a Changjiang Scholars Chair Professor. He has also held Visiting positions with the University of Toronto, Toronto, ON, Canada and Lehigh University, Bethlehem, PA, USA. His research interests include intelligent control, renewable energy systems, smart grid, and industrial big data. He has been serving as an Associate Editor for the IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Neural Networks and Learning Systems, Transactions of the Institute of Measurement and Control, and Automatica Sinica.

Chair: Prof. Yanhong Luo Northeastern University,China

Biography

Yanhong Luo is a Professor and Doctoral Supervisor with Northeastern University. She is selected in the National Youth Talent Plan, the Standing Director of IEEE PES (China) Smart Grid and Artificial Intelligence Sub-Committee, and the Vice Chairman of IEEE Adaptive Dynamic Programming and Reinforcement Learning Technical Committee (2015-2016). She has published more than 100 papers, of which 7 are ESI Highly Cited Papers, 60 are indexed by SCI. She has also published 2 monographs, and more than 20 national invention patents are authorized. She has been engaged in the research of adaptive dynamic programming, distributed optimal control of energy Internet, high proportional accommodation of distributed energy, aggregation and optimization of virtual power plants, etc. She has undertaken 5 projects of National Natural Science Foundation/Key subprojects and national key R&D subprojects, and 3 projects are specially supported by the Ministry of Education and China postdoctoral Science Foundation/Postdoctoral Special Funding. There are 4 general and key Fundamental Research Funds for the Central Universities of the Ministry of Education, as well as more than 20 projects in large-scale electric power enterprises. She has won the Andrew P. Sage Best Paper Award of the IEEE SMC Society in 2015 and the Best Paper Award of International Journal “Guidance, Navigation and Control” in 2022. She has also won the Second Prize of National Natural Science Award of China in 2020 (ranked second), the First Prize of Natural Science Award of Chinese Association of Automation in 2017, the First Prize of Scientific and Technological Progress Award of Chinese Association of Automation in 2020, the First Prize of Natural Science Award of Liaoning Province in 2015 and the gold medal of 2025 Geneva International Invention Exhibition, and served as the Chairman/Keynote Speaker and the TPC member at more than 10 international conferences.

Abstract

Robots are revolutionizing manufacturing, healthcare, logistics, agriculture, or even home. The rise of robots has created huge demands and opportunities for robotics talent, and has stimulated great interests in robotics research from both academia and industries. With the accumulation of practical experience, technology advances, and the wide spread applications, robots of the future will be more intelligent, connected, collaborative, and mobile. The objective of this session is to provide a forum for researchers to discuss and disseminate research work related to emerging technologies that are defining the future of robotics.

Chair: Dr. Jingbing Zhang Advanced Remanufacturing and Technology Centre (ARTC) and Singapore Institute of Manufacturing Technology (SIMTech), A*STAR, Singapore

Biography

Dr. Jingbing Zhang is currently the R&D Director of Smart Robotics and Automation Division, ARTC and SIMTech, A*STAR, Singapore. He is responsible for developing strategy and leading robotics R&D and industrial applications for the two research institutes. He is a member of the Technical Advisory Group (TAG) of Singapore’s National Robotics Program (NRP) office. Prior to joining ARTC, he was a Research Director at IDC Asia Pacific, responsible for leading IDC's worldwide robotics and Asia Pacific manufacturing research programs. From 2008-2015, he worked as a Senior Engineering Director at K&S HQ in Singapore, where he provided site leadership, coaching, and mentoring to the Singapore engineering R&D department. From 1992-2008, he worked in Singapore Institute of Manufacturing Technology (SIMTech), with increasing responsibilities as manager of various research groups, director, and member of the institute’s management committee. His research interest and expertise include robotics, Industry 4.0, IIoT, smart manufacturing, MES, and logistics system automation.

Dr Zhang earned a B.Eng. degree in industrial automation from Tsinghua University in 1985, a Ph.D. degree from Loughborough University, UK, in 1992, and an MBA degree (with Distinction) from the University of Birmingham, UK, in 2001. He has completed the International Executive Program at INSEAD (France/Singapore) in 2006/2007. In 2003, he received the Prestigious Engineering Achievement Award from the Institution of Engineers Singapore (IES) in recognition of his outstanding contribution to the full automation of Singapore Airlines’ air freight terminal 6 (Singapore Airlines Super Hub 2).

Dr Zhang is a senior member of IEEE and has served as AdCom member of the IEEE Industrial Electronics Society, Chair/vice-chair of IEEE IES Singapore Chapter, Associate Editor of IEEE Transactions on Industrial Electronics, General Chairs of INDIN2006, ICIEA2010, ICIEA2015, Financial Chairs of ICIEA (multiple editions), Financial Chair/TPC Chair of IECON2020/2023, and so on. He has over 80 technical publications in peer reviewed journals and conferences.

Chair: Dr. Zhengguo Li Institute for Infocomm Research, Singapore

Biography

Zhengguo Li (F’23) received the B.Sci (Applied Mathematics). and M.Eng. (Automatic Control) from Northeastern University, Shenyang, China, in 1992 and 1995, respectively, and the Ph.D. degree (Automatic Control) from Nanyang Technological University, Singapore, in 2001.

His researchinterests include video processing and delivery, computational photography, switched and impulsive control, sensor fusion and physics-driven deep learning. He has co-authored one monograph, more than 200 journal/conference papers including more than 60 IEEE Transactions, and eleven granted USA patents, including normative technologies on scalable extension of H.264/AVC and HEVC. He has been actively involved in the development of H.264/AVC and HEVC since 2002. He had three informative proposals adopted by the H.264/AVC and three normative proposals adopted by the HEVC. Currently, he is with the Agency for Science, Technology and Research, Singapore.

Zhengguo served as a TPC Chair of IEEE IECON 2023 and 2020, a special session chair of IEEE ICASSP 2022, a Technical Brief Co-Founder of SIGGRAPH Asia, and leading Workshop Chair of IEEE ICME in 2013. He was an Associate Editor of IEEE Signal Processing Letters from 2014-2016, IEEE Transactions on Image Processing from 2016-2020, IEEE Transactions on Circuits and Systems for Video Technology from 2020-2023, APSIPA Transactions on Signal and Information Processing from 2022-2025, an editor of MDPI Sensors from 2022-2024, and a Senior Area Editor of IEEE Transactions on Image Processing from 2020-2024.

Abstract

"The 'New Generation of Artificial Intelligence' realizes the twin evolution and reverse reasoning of virtual and actual manufacturing operations based on the industrial Internet. It innovatively integrates and aggregates data from various elements of complex manufacturing systems, providing methods to solve the challenges of intelligent control and scheduling in the open environment of the industrial Internet of Things. It breaks through the problem of large-scale intelligent technology in cost reduction and efficiency improvement, and addresses the technology of group intelligent optimization decision-making. Starting from both theoretical and practical perspectives, this topic discusses the research status, progress, achievements (theory and experiment) and challenges of industrial Internet and "new generation artificial intelligence" related technologies in intelligent perception, intelligent control, intelligent scheduling and artificial intelligence safety.

Chair: Prof. Yingwei Zhang Northeastern University, China

Biography

Yingwei Zhang received the B.S. degree from the Harbin Institute of Technology, Harbin, China, in 1993, and the Masters and Ph.D. degrees in control theory and control engineering from Northeastern University, Shenyang, China, in 1998 and 2000, respectively. She was a Postdoctoral researcher with Northeastern University from March 2001 to December 2003, and was promoted to Associate Professor in 2002. Since 2010, she has been a Professor with the State Laboratory of Synthesis Automation of Process Industry, Northeastern University, ShenYang, China. She was supported by National Science Fund for Distinguished Young Scholars in 2013. Her current research interests include intelligent fault detection, artificial intelligence safety, resource scheduling and intelligent control.

Abstract

Researchers and specialists in the areas related to the IntelliSense and Advanced Sensing, Detection Technology will present their original research results covering the following topics: Intelligent monitoring and fault diagnosis in the process of production; Novel sensing theory, methods and technology; Advanced detection technology, intelligent instrument and apparatus; Internet of Things based intelligent sensing system theory and technology; Machine vision and intelligent information processing; Automatic identification methods and technology for biological feature; Monitoring, detection and sensing technology in Intelligent Transportation; Monitoring, detection and sensing technology in Smart Power Grids; IntelliSense and sensing technology in robot; Sensing technology and systems in intelligent diagnosis and treatment; Smart home and IntelliSense; IntelliSense and wireless sensor network; Smart skin, intelligent, eyes, smart.

Chair: Prof. Yong Zhao Northeastern University, China

Biography

Yong Zhao received his M.A. and Ph.D. degrees, respectively, from the Harbin Institute of Technology, China, in 1998 and 2001. He was a postdoctoral fellow in Department of electronic engineering, Tsinghua University from 2001 to 2003, and then worked as an associate professor in the Department of Automation, Tsinghua University from 2003 to 2009. Now he is working in Northeastern University as a full professor, and the president of Northeastern University at Qinhuangdao. In 2015, he was honored as the Yangtze River Scholar Distinguished Professor by the Ministry of Education of China. In 2014, he was awarded by the National Science Foundation for Distinguished Young Scholars of China. In 2008, he was awarded as the “New Century Excellent Talents in University” by the Ministry of Education of China. As an academic leader in the field of optical fiber sensing and photoelectric detection technology, he has published more than 200 high-level academic papers, been authorized more than 50 invention patents. He won two first prize and four second prizes of provincial and ministerial natural science awards, one second prize of provincial and ministerial teaching achievement awards, and published six monographs and textbooks. He is the deputy director of the State Key Laboratory of Synthetical Automation for Process Industries, the vice chairman of the National Engineering Research Center for Offshore Oil and Gas Exploration. He is an associate editor-in-chief of ACTA AUTOMATICA SINICA, and the vice chairman of the Components Branch of China Instrument and Control Society.

Abstract

The metallurgical industry, which primarily includes ferrous metallurgy and non-ferrous metallurgy, is a fundamental sector for both the national economy and defense construction, and it also provides the essential foundation for the rapid development of various industries. Thus, this special session originates from the urgent need to improve quality, enhance efficiency, and conserve energy for modern metallurgical industries. Facing the complicated dynamic characteristics of metallurgical processes such as steel and non-ferrous metallurgy, which are ‘difficult to modeling’, ‘lack of information’, ‘lack of adjustment, ‘large lag’, ‘uncertain time-varying’ and others, this special session explores operational optimization and control methods aimed at achieving green, efficient operation and high-quality development for complicated metallurgical processes. Moreover, it focuses on the theoretical and methodological approaches of operational optimization and control for complicated metallurgical systems driven by artificial intelligence.

Chair: Prof. Ping Zhou Northeastern University, China

Biography

Dr. Ping Zhou is a full professor and doctoral supervisor at Northeastern University of China and selected as a national-level young talent, and recognized at the hundred-lever of the “Hundred, Thousand, Ten Thousand Talents Program” in Liaoning Province. Dr. Zhou is mainly engaged in research on the automation, intelligentization and engineering applications of the process industry. Dr. Zhou has published over 150 journal articles in IFAC journals such as Automatica, CEP and JPC, and in IEEE Transactions including IEEE T CST and IEEE T ASE, as well as domestic journals like Science China: Information Sciences and Acta Automatica Sinica. He has published 4 academic monographs and holds more than 50 authorized invention patents in China and the United States, and has also received the inaugural Outstanding Doctoral Dissertation Award and the Young Scientist Award from the Chinese Association of Automation (CAA). In recent years, Dr. Zhou has been honored with six major research awards, including the CAA Natural Science First Prize, the Ministry of Education Natural Science First Prize, the Zhejiang Provincial Science and Technology Progress First Prize, the CAA Science and Technology Progress Special Award and others.