Special Sessions

Abstract

Connected and automated vehicles (CAVs) have the ability of gathering and sharing traffic information and vehicle state with neighboring vehicles. With the advent and increasing maturity of V2X, CAVs are believed to be a promising 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 ITSs from both theoretical and practical perspectives.

Chair: Prof. Ge Guo Northeastern University,China geguo@yeah.net

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, in1994 and 1998, respectively. He has published over 200 international journal papers within his areas of interest, which include operation optimization of intelligent transportation systems, cyber-physical systems, etc.
Dr. Guo is an Associate Editor of the IEEE Transactions on Intelligent Transportation Systems, the IEEE Transactions on Intelligent Vehicles, the Information Sciences, the IEEE Intelligent Transportation Systems Magazine, the ACTA Automatica Sinica, the China Journal of Highway and Transport and the Journal of Control and Decision. He was an honoree of the New Century Excellent Talents in University, Ministry of Education, China, in 2004, and a nominee for Gansu Top Ten Excellent Youths by the Gansu Provincial Government in 2005. 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 and machine learning, 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 xli@tongji.edu.cn

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. From 2016 to 2020, he has been a research fellow at NTU, Singapore, and he has also been a senior research associate at CityU, Hong Kong, in 2018. He held a visiting position at King Abdullah University of Science and Technology, Saudi Arabia, in Sept. 2019. He is in the finalist of IEEE RCAR 2018 and an associate editor of Journal of Control and Decision. His research interests include distributed control and optimization, game theory, and machine learning, as well as applications to UAVs and autonomous vehicles. He has published more than 50 SCI journal papers, and is a member of AAAI, CAA, CAAI, and a senior member of 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: Associate Prof. Yuanzheng Li Huazhong University of Science and Technology, China Yuanzheng_Li@hust.edu.cn

Biography

Yuanzheng Li is a joint doctor of the University of Liverpool in UK and South China University of Technology, visiting scholar of the University of Manchester in UK and Nanyang University of Technology in Singapore, 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 (founded with 112 years, and his paper was selected as an annual featured article). 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 Youxiu 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 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 sxliu@mail.neu.edu.cn

Biography

Shixin Liu received his B.S. degree in Mechanical Engineering from Southwestern Jiaotong University, China in 1990, M.S. degree and Ph. D. degree in Systems Engineering from Northeastern University, China in 1996, and 2000. He is currently a Professor of the State Key Laboratory of Synthetical Automation for Process Industries, and the College of Information Science and Engineering, Northeastern University, China. His research interests are in intelligent optimization algorithm, machine learning, computer vision, theory and method of planning and scheduling. He has over 100 publications including 1 book.

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 najing25@163.com

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 a committee member of the Process Control Association of the Chinese Society of Automation, 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 been awarded over 5 NSFC projects, published one monograph in Elsevier, more than 100 refereed papers, and authorized more than 10 invention patents. He is currently the Associate Editor of IEEE TIE and Neurocomputing, served as the Program Chairman of ICMIC 2017, Program Co-chairman of DDCLS 2019. 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 and doctoral supervisor at China University of Mining and Technology, selected by the Jiangsu Province “Six Talent Peaks” High-level Talent Selection and Training Program. He is currently a director of the Jiangsu Society of Automation, a member of the Process Control Committee of the Chinese Association of Automation, a member of the Fault Diagnosis and Safety Committee of the Chinese Association of Automation, a member of the Intelligent Simulation Optimization and Scheduling Committee of the Chinese Society of Simulation, etc. His main research interests are intelligent modeling, control and optimization of complex industrial processes, operation state evaluation and machine learning. He has published more than 80 papers in IEEE TNNLS, IEEE ASE, Acta Automatica Sinica and other journals, published 2 monographs, authorized 15 invention patents as the first inventor, 6 software copyrights, presided over more than 20 projects at the national, provincial and ministerial levels and entrusted by enterprise technology committees, and won more than 10 awards such as the First Prize of Science and Technology Progress Award of the Chinese Association of Automation, the Second Prize of Technology Invention Award of the China Nonferrous Metals Industry Science and Technology Award, and the National Coal Education Teaching Achievement Award.

Chair: Prof. Jiande Wu Yunnan University, China

Biography

Jiande Wu , as the vice president of Yunnan University, he was selected as the "Yunnan Provincial Ten Thousand People Plan Industry and Technology Leader", "Young and Middle-aged Academic and Technological leader of Yunnan", and "Yunnan Provincial First Group of Experts with Grassroots Workstation". He was also a member of the Automation Academic Committee of China Nonferrous Metals Society, a member of the Process Control Professional Committee of China Society of Automation, a member of the Multiphase Flow Test Professional Committee of the China Metrology and Testing Society, the director of China Nonferrous Metals Industry Intelligent System and Advanced Control Engineering Research Center, the executive director of the Yunnan Mineral Pipeline Conveying Engineering Technology Research Center, the chief professor of science and technology innovation team of complex system intelligent detection and control in Universities of Yunnan Province.

His main research interests are analysis and mining of industrial big data, complex industrial process detection, control and optimization. He has directed more than 30 projects founded by the National Natural Science Foundation of China, Yunnan Province and enterprise. He has published more than 60 papers with first or corresponding authorship (including more than 40 SCI/EI indexed papers), granted more than 40 patents (including more than 10 invention patents), won the second prize of the National Science and Technology Progress Award, one China Industry-University-Research Cooperation Innovation Award, one Yunnan Province Technology He was awarded the second prize of National Science and Technology Progress Award, the second prize of China Industry-University-Research Cooperation Innovation Award, the second prize of Yunnan Provincial Technology Award and the second prize of Science and Technology Progress Award.

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 sunqiuye@ise.neu.edu.com

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.

Prof. Dakuo He Northeastern University, China

Abstract

The Peripheral drive thickener is the key metallurgical production equipment for upstream-downstream anti-interference and bottleneck production, and its internal detection, optimization and control is the "bottleneck" problem to realize the substitution of domestic equipment. In response to the above problems, this report proposes to utilize pressure sensors to perceive the internal operating state of the thickener, which solves the problem of detecting and predicting key variables such as the internal ore mass. On the basis of the data-driven thickener feeding prediction technology, and with the goal of minimizing energy consumption, the optimization control technology of layered ore drawing is developed. Aiming at the abnormal working conditions of the thickener and the problems of underflow emptying and blockage, the abnormal working conditions identification technology of thickener was developed. This is the first time in China to realize the intelligent optimization control of the thickening-dewatering process, which solves the "bottleneck" problem of the key equipment of metallurgy process and effectively promotes the development of domestic independent research and development of metallurgical process equipment, and provides a crucial technical support for independent and controllable metallurgy equipment.

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, and a member of the Automation Special Committee of the Chinese Society of Non-ferrous Metals. As the project leader, he has undertaken 4 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, 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

This topic has been held for the tenth 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. Yahui Wang Beijing University of Civil Engineering and Architecture, China yahui-wang@vip.sina.com

Biography

Yahui Wang , Professor, School of Electrical and Information Engineering, 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 National Technical Committee for Standardization of Electrical Installations in Buildings (SAC/TC205)，Member of the Weak Current Professional Committee of the National Engineering Construction Standard Design Expert Committee，Member of the Professional Evaluation Committee of senior professional titles in Ministry of Housing and Urban-Rural Development，Member of the Standing Committee of The Emergency Management Professional Committee of China Excellent Selection Law And Economic Mathematics Society，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.

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

Biography

Hongyan Ma ，is a professor and deputy dean with the School of Electrical and Information Engineering, 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 CES, member of CPSS, member of CAC, 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 50 papers, edited and written 10 books.

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

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. Dingyu Xue Northeastern University,China xuedingyu@mail.neu.edu.cn

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, 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 was among the earliest toolboxes in fractional-order control community and the recent versions are used extensively by the researchers worldwide.

Chair: Prof. Jun-Guo Lu Shanghai Jiao Tong University,China

Biography

Jun-Guo 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.

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 yangdongsheng@mail.neu.edu.cn

Biography

Prof Dongsheng Yang ，is the doctoral supervisor and deputy director of the Department of Electrical Engineering, College of Information Science and Engineering at Northeastern University. 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 qmyang@zju.edu.cn

Biography

Qinmin Yang received the Bachelor's degree in Electrical Engineering from Civil Aviation University of China, Tianjin, China in 2001, the Master of Science Degree in Control Science and Engineering from Institute of Automation, Chinese Academy of Sciences, Beijing, China in 2004, and the Ph.D. degree in Electrical Engineering from the University of Missouri-Rolla, MO USA, in 2007. From 2008 to 2009, he was an advanced system engineer with Caterpillar Inc. From 2009 to 2010, he was a Post-doctoral Research Associate at University of Connecticut. Since 2010, he has been with the State Key Laboratory of Industrial Control Technology, the College of Control Science and Engineering, Zhejiang University, China, where he is currently a professor. He has also held visiting positions in University of Toronto and Lehigh University. He has been serving as an Associate Editor for IEEE Trans. on Systems, Man, and Cybernetics: Systems, IEEE Trans. on Neural Networks and Learning Systems, and Transactions of the Institute of Measurement and Control. His research interests include intelligent control, renewable energy systems, smart grid, and industrial big data.

Chair: Prof. Yanhong Luo Northeastern University,China luoyanhong@ise.neu.edu.cn

Biography

Yanhong Luo is a Professor and Doctoral Supervisor with Northeastern University. She is the Leading Talent of Shenyang, 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 2014 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 jbzhang2008@gmail.com

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 ezgli2019@gmail.com

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 zhangyingwei@mail.neu.edu.cn

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 esearcher 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

In modern industrial production, to make the equipment work well and achieve the best quality in the normal state or the best state, it is needed to use a variety of detection technologies to intellisense and control various parameters of the production lines. Now the sensor industry is at a critical stage of developing miniaturized, multi-functional, digital, intelligent, systematic and networked sensors.

This special session is positioned to give a snapshot of the current state of the art in the field of sensing, instrumentation and related fields, particularly from the applied perspective, and is also intended to give a broad overview of the latest developments, in addition to discussing the process through which researchers go through in order to develop sensors, or related systems, which will become more widespread in the future.

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 zhaoyong@ise.neu.edu.cn

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 Tsinghua University from 2001 to 2003, and then worked as an associate professor in the Department of Automation, Tsinghua University of China. In 2006, he was a visiting scholar of University of Illinois in Urbana and Champagne, USA. In 2008, he was awarded as the “New Century Excellent Talents in University” by the Ministry of Education of China. In 2009, he was awarded as the “Liaoning Bai-Qian-Wan Talents” by Liaoning Province. In 2011, he was awarded by the Royal Academy of Engineering as an academic research fellow of City University London. In 2014, he was awarded by the National Science Foundation for Distinguished Young Scholars of China. In 2015, he was honored as the Yangtze River Scholar Distinguished Professor by the Ministry of Education of China. Now he is working in Northeastern University as a full professor. As the academic leader and director of his research institute, his current research interests are the development of fiber-optic sensors and device, fiber Bragg grating sensors, novel sensor materials and principles, slow light and sensor technology, optical measurement technologies. He has authored and co-authored more than 260 scientific papers and conference presentations, 24 patents, and 5 books. He is an associate editor-in-chief of ACTA AUTOMATICA SINICA, and a member in the Editorial Boards of the international journals of Sensor Letters, Instrumentation Science & Technology, Journal of Sensor Technology, and Advances in Optical Technologies.

Abstract

The metallurgical industry includes ferrous metallurgy and non-ferrous metallurgy, which is the pillar industry of the national economy and has a profound impact on all aspects of people's social life. Starting from the urgent needs of modern metallurgical industry to achieve quality improvement, efficiency increase, energy saving and consumption reduction, and aiming at the ‘difficult to modeling’, ‘lack of information’, ‘lack of adjustment, ‘large lag’, ‘high dynamics’ and other comprehensive and complex characteristics in ferrous and non-ferrous metallurgical systems. This special session will discuss operational optimization and control methods for the green and efficient operation and high-quality development of complex metallurgical systems, focusing on the theory and methods of AI driven operational optimization of complicated metallurgical processes.

Chair: Prof. Ping Zhou Northeastern University, China zhouping@mail.neu.edu.cn

Biography

Dr. Ping Zhou is a full professor and doctoral supervisor at Northeastern University of China. He holds several high-profile honors, including National High-level Personnel of Special Support Program (Ten-Thousand Talents Program)-Outstanding Young Scholars, ‘Xing Liao Talents’ and hundred-lever of ‘Countless Talents Project’ in Liaoning Province. He also serves as a senior member of IEEE, member of IFAC MMM Technical Committee (TC 6.2) and member of ‘RNNLS’ working group of IEEE CIS NNTC. He has long been committed to the research of complex industrial process operation optimization control, data-driven modeling and control of industrial applications. He has published 3 academic monograph and published more than 100 journal articles. He has authorized more than 40 invention patents in China and the United States, and registered more than 10 computer software copyrights. Moreover, He has won the first and second prizes in Natural Science Award from the Ministry of Education of China, the first prize in Natural Science Award of Chinese Association of Automation, and the first prize in Science and Technology Progress Award from Zhejiang Province.