CCDC 2022
15-17 August

Forums

Forum 1. Women in Control and Decision Forum

Abstract

The Women in Control and Decision (WICD) forum is aimed to promote the visibility of outstanding women researchers, improve the collaborations and initiatives to advance women’s influence in Control and Decision, foster discussions on the role of women in the related research areas. The forum is planned to be organized periodically during CCDC. In CCDC 2022, three or four guest speakers will be invited to present their recent results and share their experiences/histories as women in Control and Decision. By attending the forum, young female researchers can have the chance to network and communicate with senior faculty members.

Chair: Prof. Wei WANG

Beihang University, China

Biography

Wei WANG received her B.Eng degree in Electrical Engineering and Automation from Beihang University (China) in 2005, M.Sc degree in Radio Frequency Communication Systems with Distinction from University of Southampton (UK) in 2006 and Ph.D degree from Nanyang Technological University (Singapore) in 2011. From January 2012 to June 2015, she was a Lecturer with the Department of Automation at Tsinghua University, China. Since July 2015, she has been with the School of Automation Science and Electrical Engineering, Beihang University, China, where she is currently a Full Professor. Her research interests include adaptive control of uncertain systems, distributed cooperative control of multi-agent systems, secure control of cyber-physical systems, fault tolerant control, and robotic control systems. Prof. Wang received Zhang Si-Ying Outstanding Youth Paper Award in the 25th Chinese Control and Decision Conference (2013) and the First Prize of Science and Technology Progress Award by Chinese Institute of Command and Control (CICC) in 2018. She has been serving as the Principle Investigator for a number of research projects including the National Science Fund for Excellent Young Scholars of China (2021-2023). She is an Associate Editor of the Journal of Control and Decision.

1.1 Quantum state estimation filtering and their optimization algorithms

Prof. Shuang CONG

University of science and technology of China, China

Abstract

The collapse characteristic of quantum measurement makes the number of complete measurements required for a quantum state tomography increase exponentially with the increase of quantum bits, which leads to the time-consuming processing of measurement data. For many years, it restricts the estimation and reconstruction of high qubits in the realizations of quantum control systems, affects the implementation of high-precision quantum state feedback control system, and becomes a bottleneck problem in the applications of quantum computing and quantum information. In this talk, the problem of quantum state tomography is transformed into a kernel optimization problem of quantum state density matrix estimation under quantum state constraints. Aiming at the reconstruction of quantum states with white noise and sparse disturbance in quantum system measurement, the estimation and filtering of fixed states of high qubits, and the real-time online estimation and filtering of quantum states varying with time, based on the compressed sensing theory, in reducing the number of quantum state tomography measurements, proposing fast and efficient optimization algorithms, and reconstructing quantum states with high precision, given a series of comprehensive solutions.

Biography

Shuang CONG received her Ph.D. degree in System Engineer from the University of Rome “La Sapienza”, Italy. She is a Professor in the department of automation, University of science and technology of China. She has been engaged in the researches of motion control since 1989 and quantum system control theory and method since 2000. So far, she has published more than 500 papers in academic journals and conferences in quantum system control theory and methods, advanced control strategies and their applications in motion control, and optimization algorithms, 13 scholar monographs and textbooks,19 national invention patents. She won the Excellent Young Scholar of the Chinese Academy of Sciences, the second prize of Anhui natural science, and the first prize of Anhui science and technology excellent paper. Now she is the member of control design technical committee of IFAC; the Vice Chairman of technical committee on system simulation of Chinese Association of Automation (CAA); the member of technical committee on control theory of CAA.

1.2 Complex multi-objective optimization algorithm and its applications

Prof. Jing Liang

Zhengzhou University, China

Abstract

In our daily life and industrial production, there are many optimization problems. These problems often have complex characteristics such as multi-objective, highly constrained, and multimodal properties. Evolutionary computation methods don’t need detailed function information of the problems and their parallel search ability is relatively strong. Therefore, they have been widely used in multi-objective optimization, constrained optimization, and multimodal optimization problems. This report will introduce the basic concept of evolutionary computing, benchmark functions, multimodal multi-objective optimization, constrained multi-objective optimization, and constrained multimodal multi-objective optimization algorithms and related applications.

Biography

Jing Liang is a Professor at Zhengzhou University, China. She is the Dean of School of Electrical Engineering. She received the B.E. degree from Harbin Institute of Technology, China, and the Ph.D. degree from the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. Her main research interests are evolutionary computation, swarm intelligence, multi-objective optimization, and neural network.

Prof. Liang is a senior member of IEEE, member of the IEEE Computational Intelligence Society (CIS), and a member of the IEEE Computational Intelligence Society Emergent Technology Technical Committee (IEEE CIS ETTC). She has obtained the NSFC Outstanding Youth Science Fund Project. She won the IEEE CIS Outstanding Ph.D. Dissertation Award, the Second prize of Natural Science Award of Ministry of Education, Classic Papers: Articles That Have Stood The Test of Time (Top 1 in Evolutionary Computation), Outstanding Young Science and Technology Experts in Henan Province, High-Level Talents in Henan Province, Chief Science Popularization Expert of Henan Province, and IEEE Transactions on Evolutionary Computation (TEVC) Outstanding Associate Editor.

She served as the Associate Editor of IEEE Transactions on Evolutionary Computation (2018-Present), IEEE Transactions on Systems Man and Cybernetics: Systems (2021-Present), Swarm and Evolutionary Computation (2016-Present), IEEE Computational Intelligence Magazine (2012-2017), and Deputy Director of Journal of Zhengzhou University (Engineering Science) (2015-2019).

1.3 Unmanned Surface Vehicle Swarm Control in Complex Sea Conditions

Prof. Shaorong Xie

Shanghai University, China

Abstract

The Unmanned Surface Vehicle (USV) has the characteristics of high efficiency, low cost and reliable safety. Furthermore, USV Swarm has more accurate sensing ability, larger working range and task completion capability. The USV Swarm plays an important role on searching and rescuing missions, escort and Anti-submarine tasks at sea. The environment is complex and changeable. Complex environmental and weather conditions as well as the high mobility of USV bring challenges to target identification and tracking. There is an urgent need to solve the difficult problem of stable control of the view field of the targets with weak characteristics, information loss, and difficult detection under complex sea environments and to achieve high accuracy target detection and stable tracking. Fully acquisition of target information is important to optimize the control decision. How to realize information interaction and heterogeneous information fusion under the time-varying multi-USV collaboration is another difficult problem. Task allocation and plan guarantee the accomplishment of the USV swarm mission. Task allocation and behavior Planning of multi-USV ensuring the dynamic response and real-time performance to environmental change is the third difficult problem. Aiming at the aforementioned difficult problems, this report focuses on the detection and tracking of moving targets in the complex ocean environment, the interaction and fusion of multi-USV collaborative information, and multi-USV task allocation and planning.

Biography

Prof. Shaorong Xie is Dean of School of Computer Engineering and Science, Director of Engineering Research Center of Marine Intelligent Unmanned System Equipment of the Ministry of Education. Her main research areas are intelligent and autonomous robots, including unmanned surface vehicle technology, cooperative control technology of multi-autonomous robots, and intelligent systems. She was selected as a leading talent in Shanghai, Shanghai outstanding academic leader, and other talent plans. Among the awards Prof. Xie has received are: the first national team of Huang Danni-style teachers, the National Able Women Achievement Medal, Best Professor Award in Shanghai, Distinguished Young Scholar by the National Science Foundation of China, Young Scientist Award from the Chinese Society of Automation, Shanghai Science and Technology Elite Nomination, the second prize of national technology invention, the first prize of Shanghai science and technology advances, and the first prize of Shanghai technological invention. She is an associate editor of IEEE Transactions on Automation Science and Engineering, and an organizing committee’s member of IJCAI (International Joint Conferences on Artificial Intelligence) 2024.

1.4 Intelligent monitoring for operating conditions of major equipment

Prof. Chunhui Zhao

Zhejiang University, China

Abstract

During the actual operation of major equipment, it is a normal activity to frequently change the process operating conditions. Therefore, the operation of major equipment has distinct complex operation characteristics of "large-scale non-stationary" changes. The safe and efficient operation of major equipment urgently requires a set of theoretical methods for intelligent monitoring of operating conditions that can accurately characterize operating characteristics, accurately identify state changes, and accurately diagnose the root cause of faults in large-scale non-stationary changes. This report will introduce the theoretical method of intelligent monitoring for major equipment which overcomes the technical bottleneck that is difficult to accurately identify the operating conditions under a wide range of non-stationary changes. The intelligent monitoring system developed has been successfully applied to high-precision injection molding machines and ultra-supercritical thermal power units, which has significantly improved the key performance parameters, safety reliability and product quality rate, and provided effective solutions for the safe and efficient operation of major equipment.

Biography

Chunhui Zhao , Qiushi Distinguished Professor, Recipient of the National Outstanding Youth Fund. 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 160 papers in peer-reviewed international journals. She has published 3 monographs and authorized more than 50 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 and other provincial and ministerial awards. She also received more than ten academic awards, including the First Prize of Natural Science of Chinese Association of Automation, the First Young Women Scientists Award of Chinese Association of Automation, 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.


Forum 2. Summit forum on decision-making theory in the era of digital economy

Chair: Prof. Zeshui Xu

Sichuan University, China

Abstract

Digital economy has become an important engine to lead global economic and social change, improve the modernization of governance ability, and promote the high-quality development of China's economy. Facing the new relations in the digital economy, this forum focuses on the decision-making behaviors among the main economic subjects such as the government, producers and retailers, platforms and consumers in the development of the digital economy, dedicating to revealing the evolution pattern of decision-making theory in the digital economy era. It is of great significance to enrich the decision-making theory and promote its development and the change of research paradigm.

This forum will gather well-known experts and scholars, entrepreneurs and people of insight from all walks of life in the field of management within the branches of decision-making to focus on the basic and cutting-edge theories in decision-making within the context of digital economy, so as to explore a new paradigms of decision-making driven by digital economy. It is hoped that this session will make some contributions in promoting the rapid development of the theory and applications of decision-making within the context of digital economy.

2.1 Decision theory and application Based on Language Hedge Sets and Online Reviews

Prof. Zeshui Xu

Sichuan University, China

Abstract

With the rapid development of digital technologies such as big data, cloud computing and artificial intelligence, modern society has entered the digital economy era. The large number of online reviews generated by consumers has become one of the most important information sources affecting marketing, information systems, product development and other management activities in the digital economy era. This report focuses on research progress in decision methods based on online reviews and decision theory based on linguistic hedge sets in the digital economy era: it introduces the current state of the research in online reviews-driven decision analysis and theoretical development of the research based on linguistic hedge sets, summarizes the theoretical methods of online reviews-driven decision making based on linguistic hedge sets, and explores the applications and challenges of the linguistic hedge sets such as intuitionistic fuzzy linguistic term sets, hesitant fuzzy linguistic term sets and probabilistic linguistic term sets in online reviews-based decision analysis.

Biography

Zeshui Xu received the Ph.D. degree in management science and engineering from Southeast University, Nanjing, China, in 2003. From October 2005 to December 2007, he was a Postdoctoral Researcher with School of Economics and Management, Tsinghua University, Beijing, China. He was a Distinguished Young Scholar of the National Natural Science Foundation of China and the Chang Jiang Scholar of the Ministry of Education of China. He is currently a Professor with the Business School, Sichuan University, Chengdu. He has been elected as the member of EASA and IASCYS, Fellow of IEEE (Institute of Electrical and Electronics Engineers), Fellow of IEEE, IFSA, RSA, IET, ORS, BCS, IAAM, AAIA, and VEBLEO, and ranked 431th among World’s Top 100,000 Scientists in 2019. He has contributed more than 650 SCI/SSCI articles to professional journals, 18 monographs published by Springer, and is among the world’s top 1% most highly cited researchers with about 70,000 citations, h-index is 135. He is currently the Associate Editor of IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, IEEE Access, Information Sciences, Knowledge-Based Systems, Information Fusion, Artificial Intelligence Review, Applied Intelligence, Cognitive Computation, Fuzzy Optimization and Decision Making, Applied Soft Computing, Journal of the Operational Research Society, International Journal of Systems Science, etc. His current research interests include Intelligent decision making, information fusion, fuzzy mathematics, optimization algorithm, etc.

2.2 Multi-source Data-Driven Financial Fraud Risk Analysis

Prof. Jianping Li

University of Chinese Academy of Sciences, China

Abstract

This report mainly analyzes the impact of the big data era on the management, method, and decision-making mode of financial fraud risk analysis. It focuses on the theory, mechanism, technology, and typical cases of multi-source data-driven financial fraud risk analysis. First and foremost, it reviews the evolution of financial fraud risk analysis data from structured, semi-structured, to unstructured panoramic multi-source big data and further points out the opportunities and challenges brought by multi-source data to financial fraud risk analysis. Then it analyzes the direction of fraud risk analysis methods in response to higher multi-source data processing requirements. At last, it summarizes the main challenge still faced in the current financial fraud risk analysis.

Biography

Jianping Li is a distinguished professor of the University of Chinese Academy of Sciences; executive vice dean of the School of Economics and Management at the University of Chinese Academy of Sciences; recipient of the National Fund for Distinguished Young Scholars; He is also the secretary-general of the International Academy on Information Technology and Quantitative Management (IAITQM). Vice-chairman of the Chinese Society of Optimization, Overall Planning and Economical Mathematics (CSOOEM); Chairman of Risk Management Branch of CSOOEM; Chairman of Decision Science Branch of Operations Research Society of China; Editor-in-chief of Chinese Journal of Management Science, and Management Review, etc. His research interests focus on risk management and big data-driven decision-making. He has been awarded the "China Youth Science and Technology Award", "National Outstanding Science and Technology Worker", "Excellent Tutor Award of Chinese Academy of Sciences", and "Highly Cited Chinese Researchers from Elsevier". He has published more than 130 papers in domestic and foreign academic journals and won 2 first prizes and 4 second prizes in provincial and ministerial Natural Science/Technology Progress Awards.

2.3 Data Intelligence for Smarter City Management

Prof. Junjie Wu

Beihang University, China

Abstract

Recent years have witnessed the emergence of worldwide megalopolises and the accompanying public safety events, making urban safety a top priority in modern urban management. In this talk, the managerial dilemmas in smart cities will be discussed, and data intelligence is introduced as a cutting-edge solution. Three key components of data intelligence, i.e., data, model and scenario, will be discussed in depth with a “make & use” interactive philosophy. Two cases, namely the Hazardous Goods Management and Infectious Disease Management, will then be introduced to illustrate how to apply data intelligence to build a smarter and safer modern city, from both an academic research and practical management perspectives, with a focal discussion on their interactions. The talk will finally be extended to some pertinent and frontier topics, including Mobile IoTs, Human-Machine Interface, Distributed Intelligence, and Digital Twins.

Biography

Junjie Wu is currently a full professor of the School of Management, Harbin Institute of Technology. He is also a full professor of the School of Economics and Management, Beihang University. Dr. Wu is the recipient of various national academic awards, including the NSFC Distinguished Young Scholars and the MOE National Excellent Doctoral Dissertation. He has been engaged in interdisciplinary research of management science, computer science and social science. His research interests include data mining and artificial intelligence, with intense applications in smart city, social governance, fintech, smart healthcare, etc. His work has been prolifically published on international top journals including ISR, MISQ, TKDE and TOIS as well as top technical conferences such as KDD, IJCAI and AAAI. He holds over 20 national invention patents and 2 first-class provincial science and technology awards.

2.4 Live-streamer as A Selling Agent: Is Sales Commitment Profitable?

Prof. Yongbo Xiao

Tsinghua University, China

Abstract

With the rapid development of live-streaming commerce, it has been increasingly common for firms (including brands, manufactures, and sellers) to collaborate with live-streamers (e.g., online influencers, celebrities, or key opinion leaders) to sell their products in the live broadcasting room. Despite the great success of live-streamers acting as agents of sellers, it is not uncommon that some live-show's gross merchandise volume (GMV) falls far below its expectation, since the sales volume largely depends on the effort extent that live-streamers devoted in attracting fans and promoting products. In order to reduce the failure risk involved in live sales, the live-streaming agreement signed between the seller and live-streamer sometimes specifies the minimal sales volume, which represents the sales commitment the live-streamer makes to the seller. By doing so, the live-streamer has incentive to devote more effort and the seller has incentive to prepare more inventories. In this paper, we study the impact of such commitment on the performance of supply chains that consist of a single seller and a single live-streamer. In the stylized models under consideration, the live-streamer acts as a selling agent of the seller and determines the effort level devoted in attracting fans and promoting products, and the seller determines the inventory level to be prepared prior to the live-show. We compare the optimal decisions and corresponding expected profits for two scenarios in the absence and presence of sales commitment on the side of the live-streamer, respectively. Note that in the latter scenario, the commitment volume is to be determined by the live-streamer as well. Our research uncovers many interesting managerial insights. Furthermore, benchmarking on the centralized supply chain, we propose a set of commitment-based contracts to coordinate the seller and the live-streamer.

Biography

Yongbo Xiao is a Professor (with tenure) at School of Economics and Management, Tsinghua University, China. He received his Ph.D. and M.A. in Management Science and Engineering in 2006, and B.E. in Management Information Systems in 2000, all from Tsinghua University. He joined Tsinghua SEM as an assistant professor in Aug. 2008 after he completed his postdoctoral research in Department of Economics in Tsinghua SEM. He was awarded the “Science Fund for Distinguished Young Scholar” and “Science Fund for Excellent Young Scholar” under National Natural Science Foundation of China (NSFC) in 2021 and 2012, respectively. He was awarded the “Young Scholar Award of Chinese Management Science” in 2014, and elected as a Chang Jiang Scholar in 2015.

Dr. Xiao’s research interests include revenue and pricing management, service management, supply chain management, and healthcare management. His research topics include airline revenue management, assemble-to-order systems, fresh product supply chain management, channel integration in online retailing, demand management with product rollovers, rent-to-own contracts, and dynamic mechanism design. Dr. Xiao has published over 40 papers in the refereed international and domestic journals in the area of operations research and management science, including Operations Research, Production and Operations Management, Decision Sciences, Naval Research Logistics, and IIE Transactions.


Forum 3. Innovative Cultivation and Practice of Automation Talents

Chair: Prof. Tao ZHANG

Tsinghua University, China

Abstract

With the continuous innovation and rapid development of science and technology, the field of automation is facing major development opportunities and challenges. Therefore, the cultivation of automation talents urgently needs reform and innovation. With the theme of “Innovative Cultivation and Practice of Automation Talents”, the Automation Education Forum of this China Control and Decision Conference is very honored to invite experts and professors from famous domestic universities who have been engaged in the training of automation talents for many years to make special reports and share with us the new modes, new ideas and new methods of innovative training of automation talents, and their valuable experience and understanding in educational practice.

3.1 Facing the Frontier of Disciplines and Exploring the Cultivation of High Level Interdisciplinary Talents

Prof. Tao ZHANG

Tsinghua University, China

Abstract

The Department of Automation of Tsinghua University has always had a good tradition and solid foundation in teaching. In recent years, Artificial Intelligence, Big Data, Internet and other cutting-edge technologies have become an important driving force to promote the development of automation, and put forward higher requirements for the construction of Automation curriculum system and talent training path. In this regard, the Department of Automation takes “Control Theory, Information Theory and System Theory” as the basis, takes “+ Intelligence” as the idea, faces the frontier of the discipline, and deeply carries out the teaching reform of training high-level cross talents in the field of automation. Oriented to the major needs of the country and guided by the frontier of disciplines, the Department of Automation builds a high-quality curriculum system with growth and foresight; By taking the curriculum construction as the main line and condensing high-level teachers, the Department of Automation establishes high-quality curriculum teaching groups in different directions, and forming an advantageous teaching team combining the elderly, middle-aged and young; With the assistance of MOOC construction, the Department of Automation enriches the teaching forms and promotes the personalized training of students. The Department of Automation actively adapts to the frontier development of disciplines, boldly transforms traditional professional courses, solves important problems such as lagging curriculum system, insufficient coupling with the frontier of disciplines and weakening teaching inheritance, promotes the formation of a high-level cross talent training system, and lays a solid foundation for cultivating outstanding talents with the ability to lead future development.

Biography

Tao Zhang ,Professor, Head of Department of Automation of Tsinghua University, Deputy Dean of School of Information Science and Technology of Tsinghua University. He is a Fellow of IET/CAA, senior member of IEEE, member of Robot Working Committee of IFAC, Associate Editor of IEEE Transactions on Automation Science and Engineering, Associate Editor of IEEE Robotics and Automation Letters, council member of Chinese Association for Artificial Intelligence, council member of Chinese Association for Automation. His main research interests are robot, artificial intelligence, control theory and so on. He has presided over or participated in more than 30 projects. He has published more than 200 papers and obtained more than 20 domestic authorized invention patents. He has won the National Teaching Achievement Award, Natural Science Award of Ministry of Education, Beijing Science and Technology Progress Award,Natural Science Award of Chinese Association of Automation, Electronic Information Science and Technology Award of Chinese Institute of Electronics and so on.

3.2 Exploration and Practice for Fostering Talent of Automation in Intelligence Era

Prof. Hong Chen

Tongji University, China

Abstract

The fast iteration of automation technology provides a confluence of unprecedented opportunities: the boost-up of the industrial revolution, the creation of interdisciplinary fusion, and the birth of emerging techniques or new disciplines. Meanwhile, the fast development of the automation technology raises challenges up in technological education for talent fostering. This talk will discuss key issues of the conventional education system and introduce our exploration and practice on a new educational pattern towards intelligence era.

Biography

Hong Chen , distinguished professor at Tongji University, dean of the college of Electronic and Information Engineering, CAA Fellow, China-SAE Fellow. She was a recipient of NSFC Distinguished Young Scholar Award. From 2015 to 2019, she served as the director of the State Key Laboratory of Automotive Simulation and Control. She received the B.S. and M.S. degrees in process control from Zhejiang University, China, in 1983 and 1986, respectively, and the Ph.D. degree in system dynamics and control engineering from the University of Stuttgart, Germany, in 1997.

Prof. Chen has advised over 160 graduate students and some of her students received outstanding dissertation award. Prof. Chen is recognized internationally for her research on control theory and applications to intelligent automotive. Since recent five years, her research has been granted funding by major program of NSFC, national key R&D program and provincial key program. She is the founding director of CAA TC on Vehicle Control and Intelligence (VCI) and has been an active member of IFAC TC on Automotive Control (AC), CAA TC on Process Control (PC), CAA TC on Control Theory (CT) and CAAI TC on Society of Intelligent Aerospace Systems (SIAS).

3.3 The Exploration and Practice on the “One Body Two Wings, Innovation-driven” Training mode of Emerging-Engineering Automation Specialty

Prof. Dibo Hou

Zhejiang University, China

Abstract

Since 2017, the Ministry of Education has been actively promoting the construction of New Engineering Disciplines, formed the "Fudan Consensus", "Tianda Action" and "Beijing Guide", and issued the "Notice on Carrying Out Research and Practice of New Engineering Disciplines" and "Notice on Promoting Research and Practice Projects of New Engineering Disciplines" for exploring the Chinese model and experience of leading global engineering education. The construction of New Engineering Disciplines involves all aspects of higher engineering education, which brings unprecedented opportunities and challenges to traditional engineering majors. Due to its multidisciplinary intersection and multi-disciplinary application, Automation major is a very good pilot major for cultivating talents in New Engineering Disciplines. With the background of education reform practices of Automation major, the College of Control Science and Engineering, Zhejiang University has designed a new engineering talent training program based on the reconstruction of "one body, two wings, innovation-driven" structure, which addresses the opportunities and challenges faced by automation major under the New Engineering Disciplines strategy and combines the requirements of the New Engineering Disciplines construction and double first-class construction. The undergraduate teaching reform of the new automation major has been carried out in the aspects of synergistic development of traditional engineering and new engineering, optimization of curriculum system, reform of teaching methods, enrichment of teaching contents, cultivation of innovation ability, laboratory construction and internationalization cultivation, etc. The relevant work has certain reference significance for the construction of automation major in other institutions.

Biography

Dibo Hou , Professor and Vice Dean of the College of Control Science and Engineering, Zhejiang University. He is mainly engaged in research in the fields of advanced sensing technology, environmental monitoring and early warning, robot intelligent perception, etc. He has presided over more than 30 scientific research projects such as National Natural Science Foundation of China, National Major Science and Technology Special Project, Zhejiang Province Key Research and Development Program, Zhejiang Province Science and Technology Program Project, etc. He has won the First Prize of Zhejiang Province Science and Technology Progress Award, China Industry-University-Research Cooperation Innovation Award, China Instrument Society Science and Technology Achievement Award, etc. He is actively engaged in teaching reform, presiding over the construction of national first-class undergraduate major, leading the course "Computer Control System Design and Practice" as a high-quality course and first-class undergraduate course in Zhejiang Province. He has won the honors of advanced worker, advanced individual in teaching and education, and advanced individual in innovation and entrepreneurship of Zhejiang University. The student teams under his guidance have won the special gold medals in the Geneva International Invention Exhibition, the special prize in the Challenge Cup Competition of Science Achievement in China and the first prize in the National Student Robotics Competition.

3.4 Integrative innovation training of the students with aerospace characteristics in automation field

Prof. Bin Jiang

Nanjing University of Aeronautics and Astronautics, China

Abstract

In recent years, China's strategies such as innovation-driven development and artificial intelligence, as well as the high-level automation and intelligence developed by civil airplanes and manned spaceflights, have put forward higher requirements for engineering and technical talents. Focusing on the automation major in Nanjing University of Aeronautics and Astronautics, we strengthen the integration of aerospace characteristics and artificial intelligence, reform the curriculum system, innovate the teaching mode, and the following measures are taken for the students training: 1) make the faith education throughout the whole bachelor period. 2) construct a new curriculum system with aerospace characteristics by integrating the automation and artificial intelligence. 3) create a synthetically practicing environment. 4) found a new students training mode with international characteristics.

Biography

Bin Jiang received the Ph.D. degree in Automatic Control from Northeastern University, Shenyang, China, in 1995. He had ever been postdoctoral fellow, research fellow, invited professor and visiting professor in Singapore, France, USA and Canada, respectively. Now he is a Chair Professor of Cheung Kong Scholar Program in Ministry of Education and Vice President in Nanjing University of Aeronautics and Astronautics, China. He has served as Subject Editor of Int. J. Control. Automaton and Systems, Associate Editor or Editorial Board Member for a number of journals such as IEEE Trans. On Cybernetics, IEEE Trans. On Neural Network and Learning Systems; Neuro computing, J. of Franklin Institute, etc. He is a Fellow of IEEE, Chair of Control Systems Chapter in IEEE Nanjing Section, a member of IFAC Technical Committee on Fault Detection, Supervision, and Safety of Technical Processes. His research interests include intelligent fault diagnosis and fault tolerant control and their applications to helicopters, satellites and high-speed trains.

He has been the principle investigator on several projects of National Natural Science Foundation of China. He is the author of 8 books and over 100 referred international journal papers. He won National Natural Science Award of China.

3.5 The Cultivation Orientation and Innovative Development of Automation Talent

Prof. Qiao Junfei

Beijing University of Technology, China

Abstract

From the perspective of contributing to the economic development of the new China after 1949 and satisfying the requirements from the national defense strategy, the history of Automation Major is first reviewed. Then a comprehensive analysis of the challenges and development opportunities Automation Major faces is provided. This analysis considers the current social development background, particularly the current development situation of the Automation Major, and aims at helping implementing the strategy of invigorating China through science and education; the strategy of reinvigorating China through human resource development; and innovation-driven development strategy. Looks forward to the future, in order to proactively welcome the new round of scientific and technological revolution and industrial changes, to highlight the construction of New Engineering, and to cultivate future scientific and technological innovation leaders, several suggestions are provided finally, majorly on the future development direction and construction of Automation Major.

Biography

Qiao Junfei is currently a professor and doctoral supervisor at Beijing University of Technology. He is a member of the Discipline Appraisal Group of the State Council Academic Degrees Committee, member of the Teaching Steering Committee of the Ministry of Education, ‘Yangtze River scholars’ Distinguished Professor of Chinese Ministry of Education, recipient of the National Science Fund for Distinguished Young Scholars, selected into the National “Hundred-Thousand-Ten Thousand Talents Project”( the National Young and Mid-Aged Expert with Outstanding Contribution), and he is also an expert who receives special government allowances of the State Council.

He is mainly engaged in theoretical and applied researches on the analysis and design of neural network structure, robust control of complex systems, and multi-objective dynamic optimization. He has presided over Major Programs and Science Fund for Creative Research Groups of the National Natural Science Foundation of China respectively, and National Science and Technology Major Project of the Ministry of Science and Technology. He has more than 100 publications in top journals such as IEEE Transactions, Automatica, Acta Automatica Sinica, etc., and has been authorized more than 40 United States and Chinese invention patents. He has won many national and provincial awards such as the Second Prize of National Science and Technology Progress Award and the First Prize of Science and Technology Progress Award by Ministry of Education.

3.6 Exploration on the triple fusion talents cultivation model of automation specializing-creating collaborative

Prof. Sun Qiuye

Northeastern University, China

Abstract

To meet the country's demand for innovative and professional talents, the Northeastern University is aimed at promoting students' all-round development and solving difficulty of integration of teaching and researching, major and industry as well as theory and practice in education of automation students. Driven by innovation and entrepreneurship activities, our project takes group, curriculum and workshop into consideration. The principles of our project are: build groups on races, cultivate students in groups, treat every race as a lesson, and every race serve as a workshop. We create a "researching-innovation and entrepreneurship-teaching" system centered around the innovation groups and the integration of races and lessons, set a multi-dimensional collaborative training pattern of "competition driven - problem orientation - major integration", and establish a chain theory practice promotion platform of "innovative workshop - open practice - multidimensional evaluation". As a result, 19 collaborative innovation groups consisting of teachers and students are built, 19 courses integrating major and innovation are developed, and 19 shared and open innovation workshops are established, so as to comprehensively promote the collaborative and mutual development of major education and innovation and entrepreneurship education, and realize the four-stage talent cultivation system of "enlightenment - improvement- reinforcement - breakthrough". The outcomes of the project are based on the automation major of Northeastern University, a National First-class Special major Construction Zone and a National Innovation Experimental Area for Automation Major Talent Training Mode. The results of the project are remarkable in education and promotion and application, and has promoted the exploration of multi-dimensional talent training mode and training system with the integration of specialization and innovation and its synergistic development.

Biography

Sun Qiuye , the first batch of National Curriculum Civic Teaching Master, the first batch of national colleges and universities Huang Danian type teacher team backbone members. He enjoys the special allowance of the State Council Government, the leading talents in science and technology innovation of the National "Ten Thousand Talents", the New Century Talents of the Ministry of Education, the Specially Appointed Professor of Liaoning Province under the "Xingliao Talent Plan", the Specially Appointed Youth Entrepreneurship Mentor of Liaoning Province, and has been selected as an expert of China International "Internet+" Student Innovation and Entrepreneurship Competition. He has been awarded the national innovation and entrepreneurship practice advanced deeds task (111 people nationwide). As the first three finishers, he won more than 10 important awards such as the Second Prize of National Natural Science and the Second Prize of National Science and Technology Progress, etc. He has published more than 200 academic papers and applied for more than 100 authorized invention patents. He is currently serving as IET Follow, Secretary General of the Energy Internet Committee of the Chinese Society of Automation, and Permanent Vice Chairman of the CCDC Organizing Committee. He is also an editorial board member of IEEE TNNLS, IET CPS: T&A, Int. Trans. Electr. Energ. Syst., Automatica Sinica, Proceedings of the CSEE and other authoritative journals at home and abroad.

3.7 Exploring and Practicing Emerging Engineering Education in the Control Discipline for Catching up The Intelligent Unmanned Trend

Prof. Meiping Wu

National University of Defense Technology, China

Abstract

Given the demand for competent personnel in future intelligent warfare, this paper analyses the challenges faced by control discipline education and proposes solutions. According to the required professional ability and quality, the knowledge structure and comprehensive practice courses of majors in the control discipline have been designed, where related techniques have been integrated into the innovation practice program. As a result, the students' ability to comprehensively use intelligent unmanned systems has been improved significantly.

Biography

Meiping Wu is a professor and PhD supervisor at National University of Defense Technology, Dean of the College of Intelligent Science and Technology, chief of the “Computer Hardware Technology and Control Series Courses” national teaching group, technological innovation leading talent of “Ten-Thousands Talents Program”. He also serves as member of the Teaching Steering Committee of the Automation Major of the Ministry of Education, Vice-Chairman of the Education Committee of the Chinese Society of Automation, Executive Director of China Automation Society, and received State Council special allowance.

He has been engaged in education and research in the fields of autonomous navigation and guidance, gravity measurement, intelligent unmanned system, etc. He has published more than 100 academic papers and co-published 12 textbooks and academic monographs. He has won the second prize in the National Science and Technology Progress Award, and the first prize for teaching achievements of the Chinese Society of Automation.