CCDC 2022
21-23 May

Special Sessions

Connected Vehicle and Future Smart Transportation (Code: CVFST)

Chair: Prof. Ge Guo

Northeastern University,China

geguo@yeah.net

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.

Biography

Ge Guo , Professor and Doctoral supervisor in Northeastern University, China; Doctoral supervisor in Dalian Maritime University, China.
He received the B.S. degree in Automatic Instrument and Equipment and the Ph. D. degree in Control Science and Engineering, respectively, from Northeastern University, Shenyang, in 1994 and 1998. His current research interests include intelligent transportation systems, car-sharing and mobility systems, cooperative control of connected vehicles, cyber-physical systems, etc. He has published about 200 papers within these areas, including 40 regular papers in international journals and eight highly-cited papers. He was an honoree of the Young Scientist Award of Chinese Association of Automation, the New Century Excellent Talent in Universities in China, nominee for the Gansu Top Ten Excellent Youths, award recipient from the Fok Ying Tong Education Foundation, Qianjiang Scholar Professor of Zhejiang, Dalian Leading Talent, etc.

He is an IEEE Senior Member, Also, he serves as the Managing Editor of the International Journal of Systems, Control, and Communications, an Associate editor for Information Sciences and IEEE Intelligent Transportation Systems Magazine, and an Editorial Board Member of ACTA Automatica Sinica, Journal of Control and Decision (both Chinese edition and English edition), Journal of Control Engineering. He was awarded the Outstanding Reviewer of several journals like Annual Reviews in Control, etc.


Smart Manufacturing and Industrial Intelligence (Code: SMII)

Chair: Prof. Shixin Liu

Northeastern University,China

liushixin@ise.neu.edu.cn

Abstract

Intelligent 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; intelligent logistics and supply chains; intelligent production planning and scheduling; intelligent manufacturing knowledge management; intelligent manufacturing service management; industrial big data and its application in intelligent manufacturing; intelligent industrial robots; cyber physical system and intelligent factory.

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.


Data-driven Intelligent Optimization and Decision for Industrial Processes (Code:DIODIP)

Chair: Prof. Jing Na

Kunming University of Science and Technology, China

najing25@163.com

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.

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 , associate professor, Doctoral supervisor, deputy director of the School of Information and Control Engineering, China University of Mining and Technology. Participants of Jiangsu Province's "Six Talent Peaks" high-level talent selection and training plan, China University of Mining and Technology "Sailing Plan", and China University of Mining and Technology outstanding innovation team "Mining Area Environment and Disaster Remote Sensing" core members. Member of the Youth Working Committee of the Chinese Association of Automation, member of the Professional Committee of Fault Diagnosis and Safety of the Chinese Association of Automation, Member of the Professional Committee of Adaptive Dynamic Planning and Reinforcement Learning of the Chinese Association of Automation, Member of the Intelligent Simulation Optimization and Dispatch Committee of the Chinese Association of Simulation, Deputy Director of Process Control Professional Committee of Jiangsu Association of Automation. The research direction is intelligent modeling of complex industrial processes, control and optimization, operation status evaluation and machine learning, etc. Served as a special reviewer for many authoritative journals at home and abroad such as IEEE TNNLS, IEEE ASE, J FRANKIN I, "Acta Automation Sinica", Science China, etc., and published More than 50 papers in IEEE TNNLS, IEEE ASE, J FRANklIN I, JPC, Acta Automation, published 1 monograph, 4 invention patents authorized by the first inventor, 2 soft works, nearly 20 invention patents under application, presided over more than 10 national/provincial-level projects and participated in more than 10 horizontal projects , won the second prize of the China Nonferrous Metals Industry Science and Technology Award for Technology Invention (the first completer), the 31st CPCC Academician Zhang Zhongjun's Outstanding Paper Award (ranked 1), and the National Coal Education Teaching Achievement Award.

Advanced individual in scientific research and education of China University of Mining and Technology.

Chair: Prof. Jiande Wu

Kunming University of Science and Technology, China

Biography

Jiande Wu is currently the dean of the School of Civil Aviation and Aeronautics, Kunming University of Science and Technology. He was selected as the "Yunnan Provincial Ten Thousand People Plan Industry and Technology Leader", "Yunnan Provincial Young and Middle-aged Academic and Technical Leader". He is a member of the committee member of the China Nonferrous Metals Society, Process Control Association of the Chinese Society of Automation, the Multiphase Flow Test Professional Committee of the China Metrology and Testing Society, Director of the China Nonferrous Metals Industry Intelligent System and Advanced Control Engineering Research Center, Executive Director of the Yunnan Mineral Pipeline Conveying Engineering Technology Research Center, Chief Professor of science and technology innovation team of complex system intelligent detection and control in Yunnan Province.

His current research interests include analysis and mining of industrial big data; Measurement, control and optimization of complex industrial processes. He has been awarded over more than 20 national and municipal R&D projects, and published more than 60 papers (including more than 40 SCI/EI indexed papers), and authorized more than 40 patents (including more than 10 invention patents). He was also awarded the second prize of National Science and Technology Progress Award, China Industry-Academia-Research Cooperation and Innovation Award, and the second prize of Provincial-Ministerial Technology Invention Award.


New Energy Control and Smart Energy (Code: NECSE)

Chair: Prof. Qiuye Sun

Northeastern University,China

sunqiuye@ise.neu.edu.com

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.

Biography

Qiuye Sun , Professor and Doctoral supervisor at Northeastern University, Shenyang, China, has obtained Special Government Allowances from the State Council in China and been rewarded as one of Young and middle-aged leading scientists from the Ministry of science and technology and New Talents from the Ministry of Education in China. His current research interests include the model and optimal operation of Energy Internet, the multi-energy management and optimization of Distributed Energy System, the coordination and control of Multi-agent System, machine learning and its application in energy system, etc.

He is the secretary-general of the Energy Internet Committee in the Society of Automation, the deputy director of the New Energy Science Group the IEEE PES conference committee in China and the member of the committee of the Intelligent Energy System Committee in the Chinese Society of Artificial Intelligence, the Energy Internet Committee in the China Energy Research Institute, the committee on control and decision of cyber physical system in the Society of Automation and the Energy Internet Equipment Technology Committee in the China Electrical Technology Society. Also, he serves as the Associate Editor of IEEE TNNLS, IET CPS:T&A, IEEE Access, IEEE/CAA Journal of Automatica Sinica, CSEE Journal of Power and Energy Systems and Journal of Control and Decision.


Control and Management on Smart City (Building) (Code: D11)

Chair: Prof. Yahui Wang

Beijing University of Civil Engineering and Architecture, China

yahui-wang@vip.sina.com

Abstract

This topic has been held for the seventh 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. The main directions are: (1) Big data and cloud computing technology of smart city; (2) Self-diagnosis techniques of electrical & equipment faults in buildings; (3) Health Management of municipal engineering and equipment (such as water supply, drainage, heating, gas system and others) ; (4) Control and detection technology in underground utility tunnels; (5) Robot application technology in buildings; (6) Application of Internet of Things, wireless sensor network technology in intelligent building system; (7) Development and application research on building information model (BIM) ; (8) New technology of building fire protection and security; (9) Energy-saving technology research of building power supply, renewable energy and new energy; (10) Environmental monitoring and control technology of modern architecture; (11) Building automation (such as: building 3D printing, refabricated building); (12) Application of image and video processing and pattern recognition technology in the buildings; (13) Motion control in the building equipment and environment (such as: elevator control); (14) Process control in the building equipment and environment (such as: the control of air conditioning); (15) Application of advanced control theory in the intelligent building system; (16) Intelligent of engineering construction management; (17) Disaster prevention and mitigation and emergency decision-making of urban lifeline (power supply, water supply, drainage, heating, gas, urban rail transit and other systems); (18) City intelligent transportation and logistics.

Biography

Yahui Wang, Professor of Automation, Beijing University of Civil Engineering and Architecture. He is a leader for the constructions information and detection control engineering group. In addition, he has the following duties: Vice chairman, building robot professional committee of Chinese Association of Automation. Executive director of Beijing Association of Automation. Member of National Standardization Technical Committee for Electrical Installations of Building (SAC/TC205). Member of weak current Specialty Committee of National Engineering Construction Standard Design Expert Committee; Member of the Standing Committee of The Emergency Management Professional Committee of China Excellent Selection Law And Economic Mathematics Society (Double Law Society); Special consultant of intelligent gas Network Committee of China City Gas Association.

Research direction: Self-diagnosis of gas equipment and building electrical fault; Snake robot for pipe detection; Application of wireless sensor network system (Internet of Things) in the field of building environment and equipment; Project management and emergency management in municipal engineering.

Research achievements and awards: Over the years, the good achievements had been made in the field of building environment and equipment detection and fault diagnosis theory and practice; Over the years in the building environment and equipment detection and fault diagnosis theory and practice has made good achievements; Pioneering work in emergency management research of the area of pan-architecture; The project was supported by enterprises, the City of Beijing, the Ministry of Housing and Urban-rural Development and the National Natural Science Foundation of China. He had been teaching for more than 35 years and had been responsible for more than ten courses. He has completed more than 20 scientific research and engineering projects and won many awards. He has edited and written 10 books, published more than 100 various papers, and supervised nearly 100 post-graduate students.


Fractional Calculus and Fractional-order System (Code: FCFS)

Chair: Prof. Dingyu Xue

Northeastern University,China

xuedingyu@mail.neu.edu.cn

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.

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.


Energy big data and energy system digitalization(Code: EBDESD)

Chair: Prof. Dongsheng Yang

Northeastern University,China

yangdongsheng@mail.neu.edu.cn

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.

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.


Future Robotics Technology and Application (Code: FRTA)

Chair: Dr. Jingbing Zhang

Advanced Remanufacturing and Technology Centre, Singapore

jbzhang2008@gmail.com

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.

Biography

Dr. Jingbing Zhang , Technical Division Director of Advanced Robotics Technologies division, Advanced Remanufacturing and Technology Centre (ARTC), Singapore. He is responsible for developing strategy and leading robotics R&D and industrial application. 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 interst and expertise include robotics, Industry 4.0, IIoT, smart manufacturing, MES, and logistics system automation.

Dr Zhang earned a B.Eng. degree in automation from Tsinghua University in 1985, a Ph.D. degree from Loughborough University, UK, in 1992, and an MBA degree (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, 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 (SM’03) received the B.Sci. and M.Eng. from Northeastern University, Shenyang, China, in 1992 and 1995, respectively, and the Ph.D. degree from Nanyang Technological University, Singapore, in 2001.

His current research interests include computational photography, mobile imaging, video processing & delivery, and switched and impulsive control. He has co-authored one monograph, more than 190 journal/conference papers including more than 40 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. He is a member of SIG on computational imaging. He served a General Chair of IEEE ICIEA in 2016, a Technical Brief Co-Founder of SIGGRAPH Asia, a General Co-Chair of CCDC in 2013, leading Workshop Chair of IEEE ICME in 2013, and an Area Chair of IEEE ICIP 2016. He was an Associate Editor of IEEE Signal Processing Letters from 2014-2016 and is an Associate Editor of IEEE Transactions on Image Processing Since 2016.


IntelliSense and Advanced Sensing, Detection Technology (Code: IASDT)

Chair: Prof. Yong Zhao

Northeastern University, China

zhaoyong@ise.neu.edu.cn

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.

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.


AI-Driven Operational Optimization and Control of Metallurgical Process (Code: AOOCMP)

Chair: Prof. Ping Zhou

Northeastern University, China

zhouping@mail.neu.edu.cn

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.

Biography

Ping Zhou , Professor and doctoral supervisor at Northeastern University, 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 1 academic monograph, published more than 90 journal articles, and authorized more than 30 invention patents.