Guide
In order to fully implement the strategy of innovation-driven development and rejuvenating the country through science and education, thoroughly implement the deployment requirements of the "National New Generation Artificial Intelligence Development Plan", mobilize the enthusiasm and creativity of the majority of intelligent science and technology leading talents, promote the integrated development of general artificial intelligence and future industries, accelerate the development of new quality productivity and new industrialization, and build an industrial science and technology innovation center with global influence. From April 12th to 14th, 2024, the Chinese Society of Artificial Intelligence will hold the "'Innovation-Driven • Digital Intelligence Power' - The 13th Wu Wenjun Artificial Intelligence Science and Technology Award Ceremony and the 2023 Chinese Artificial Intelligence Industry Annual Conference" in Suzhou Industrial Park.
01
Background of the event
In recent years, with the rapid development of a new round of global scientific and technological revolution and industrial transformation, generative AI, large models and general artificial intelligence have become key areas for the emergence of new industries, new forms of business and new models. It is particularly important to promote the optimization and upgrading of the industrial chain and supply chain, strengthen the research of key core technologies of artificial intelligence, focus on solving major application and industrialization problems, actively cultivate emerging industries and future industries, strengthen the national strategic scientific and technological strength, accelerate the construction of new quality productivity, and build a digital industrial cluster with international competitiveness.
Encourage innovation and take responsibility intelligently. 2024 is the 30th anniversary of the development and construction of Suzhou Industrial Park by the Chinese government and the Singapore government, and it is also a key year for the Society to implement the spirit of the National People's Congress and the National People's Congress and the National People's Congress of the People's Republic of China, empower Suzhou to actively carry out the "Artificial Intelligence +" action, give full play to the exploration, leading and exemplary role of Suzhou Industrial Park, promote the deep integration of artificial intelligence and the real economy, and take high-quality development to a new level, strive to build a world-class high-tech park with openness and innovation, and expand exchanges and cooperation between the Society and local governments.
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Forum features
The 2023 Chinese Artificial Intelligence Industry Annual Conference China Artificial Intelligence Industry Annual Conference (CAIIAC2023) was initiated and hosted by the Chinese Industrial Intelligence Society, and has successfully held nine industry annual conferences so far. As the theme supporting activity of the Wu Wenjun Artificial Intelligence Science and Technology Award Ceremony, the conference integrates closed-door discussions, honorary commendations, high-end forums, product displays, report releases and other core sections, and is an annual artificial intelligence landmark awards event with high authority, large scale, strong brand power and far-reaching industry influence in China.
With the theme of "Innovation-driven, Digital Intelligence Power", the conference set up a "1+10+X" model, including 1 main forum, 10 special forums, as well as authoritative awards, launching ceremonies, report releases, science nights and other special activities. The organizer invites leading experts from ministries and commissions, academicians of the Chinese Academy of Sciences and the Chinese Academy of Sciences, members of Wu Wenjun's Artificial Intelligence Science and Technology Award Committee, nominating and judging experts, award-winning representatives and entrepreneurs to discuss and exchange, give full play to the academic, talent, technological and industrial advantages of the award-winning project team and the achievements of artificial intelligence colleges, and set up a special report on "Intelligent System - Artificial Intelligence President" in the theme report link, focusing on how to promote the coordinated development of artificial intelligence cutting-edge technology application and industrial ecology. By looking forward to the future trend of artificial intelligence, exchanging key core technologies and future industrial innovation, the intelligent system promotes the in-depth thinking and collision of views on the integration of industry and education in colleges and universities.
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Report Highlights:
On the morning of April 14, the organizing committee of the conference will grandly launch the special forum on "Intelligent Manufacturing and New Industrialization", and invite Professor Han Honggui of Beijing University of Technology, the first prize winner of Wu Wenjun's Artificial Intelligence Technology Invention Award, to serve as the chairman of the forum. The forum is also honored to invite authoritative scholars and outstanding experts from well-known universities and leading enterprises across the country, who have made remarkable achievements in the field of intelligent manufacturing and new industrialization, including academicians of the European Academy of Natural Sciences, winners of the National Fund for Distinguished Young Scholars, leading talents in scientific and technological innovation of the National "Ten Thousand Talents Program", and winners of the National Fund for Outstanding Young Scholars. This forum focuses on the key technologies of intelligent manufacturing and new industrialization, discusses innovative trends such as intelligent optimization control and machine learning algorithms, shares the application of artificial intelligence in resource scheduling, decision-making quality improvement, low-carbon and other technologies, and discusses the development of intelligent unmanned systems and the application challenges of network swarm intelligent collaborative learning in intelligent manufacturing. At the same time, the forum will also introduce the role of artificial intelligence in industrial operations, process manufacturing competitiveness, and industrial Internet of Things data transmission, and show the application of iFLYTEK Xinghuo model V3.5 in multiple fields and how to help new industrialization.
This forum aims to provide a platform for a comprehensive understanding of the application of artificial intelligence in intelligent manufacturing and new industrialization, promote industrial innovation and digital transformation, discuss and share the latest theories, technological breakthroughs and application practices in the field of intelligent manufacturing and new industrialization through the exchange and collision of views, help government departments, scientific research institutions, commercial enterprises, science and technology parks and financial departments to provide direction guidance and decision support, and promote the industrialization of artificial intelligence scientific and technological achievements in mainland China. Promote the high-quality development of the digital economy and the real economy, and build a high-level exchange and cooperation platform.
Here, the organizing committee of the forum sincerely invites colleagues from all walks of life to come to this conference to discuss the new changes, new opportunities and new challenges in the era of artificial intelligence.
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Agenda of the Forum
05
Forum Organizing Committee
Science Technology
Chairman of the Forum - Han Honggui
He is currently the director of the Engineering Research Center of the Ministry of Education of the "Digital Community", the director of the Beijing Key Laboratory of Computational Intelligence and Intelligent Systems, the secretary-general of the Environmental Protection Automation Professional Committee of the Chinese Association of Automation, the director of the Beijing Association of Artificial Intelligence, and the director of the Beijing Society of Automation.
Professor Han Honggui is committed to the research of theoretical methods and key technologies of intelligent optimal operation control of complex systems, focusing on intelligent feature detection, intelligent self-organizing control and whole-process collaborative optimization, etc., and has published more than 100 academic papers and 5 academic monographs in IEEE Transactions, IFAC Journals and well-known domestic journals, obtained more than 60 authorized Chinese/American invention patents and more than 50 software copyrights, presided over or participated in the formulation of national/local/ There are 11 group standards, and we have developed an intelligent optimized operation control system for complex systems with completely independent intellectual property rights, which has been successfully applied by more than 50 enterprises in different regions such as North China, East China and South China. He has won the second prize of the National Science and Technology Progress Award, the first prize of the Science and Technology Progress Award of the Ministry of Education, the first prize of Wu Wenjun's Artificial Intelligence Science and Technology Progress Award, and the first prize of the China Industry-University-Research Cooperation Innovation Achievement Award.
Science Technology
Forum moderator - Li Fangyu
Fangyu Li is a professor and doctoral supervisor at the School of Artificial Intelligence and Automation, Beijing University of Technology. National Overseas Outstanding Youth, National Key R&D Program Young Scientist. Selected as one of the top 2% scientists in the world at Stanford. At present, he is mainly engaged in the research of theoretical methods and key technologies of intelligent modeling and analysis of complex systems. The related research results have published more than 90 academic papers in well-known journals at home and abroad, and applied for more than 20 Chinese/American invention patents. He has won the Mark Weiser Best Paper Award at the IEEE PerCom Annual Conference on Pervasive Computing and the 2023 Geneva International Invention Award. He has presided over projects such as the National Key R&D Program and the National Natural Science Foundation of China. He has served as an associate editor/guest editor/editorial board member of several SCI journals, the chairman of the program committee of international academic conferences, and the chairman of international academic conference venues.
06
Invited speaker
Science Technology
Topic: Modern Pipeline Acoustic-Magnetic-Electric Fusion Detection Robot Technology
Speaker: Dong Shaohua
China University of Petroleum (Beijing), second-level professor, doctoral supervisor, academician of the European Academy of Natural Sciences. Research interests: pipeline integrity management technology, pipeline operation and maintenance technology, pipeline safety evaluation technology, and intelligent pipe network technology. Director of Pipeline Technology and Safety Research Center, Pipeline Integrity and Safety Engineering Technical Expert, "Science and Technology Leading Talent" of the National Ten Thousand Talents Program, "Young and Middle-aged Leading Talent in Science and Technology Innovation" of the Ministry of Science and Technology's Innovative Talent Promotion Program, "Shida Leading Scholar" of China University of Petroleum (Beijing), Beijing Emergency Management Discipline Leader, Beijing Advanced Discipline "Urban Energy Security and Supply Security" Leader, Xinjiang Uygur Autonomous Region "Tianshan Talent Project", Won the "70th Anniversary of the Founding of the People's Republic of China" Commemorative Medal; He has won more than 20 provincial and ministerial awards, such as the honorary title of "National Petroleum and Petrochemical Outstanding Scientific and Technological Worker", one second prize of the National Technological Invention Award, and the first prize of the Ministry of Education's Science and Technology Progress Award. He is the project leader of the National Key R&D Program, the National Major Instrument Project, and the National Natural Science Foundation of China, and has published 21 academic monographs in Chinese and English, and more than 120 academic papers.
Summary of the report
Pipeline detection is related to the safety of oil and gas transportation, and the detection technology in the pipeline mainly includes magnetic flux leakage and electromagnetic ultrasound and other related technologies. The fusion technology of ultra-high-definition magnetic flux leakage, deformation detection and centerline detection can effectively detect pipeline defects and realize the accurate positioning of girth welds; electromagnetic ultrasonic technology aims to detect the full-position defects of oil and gas pipelines, combined with phased array technology to enhance the detection ability of electromagnetic ultrasonic technology, and the fusion application of multiple technologies can realize the detection of full-position (surface/internal) defects in pipelines, especially for the detection of crack defects, which can greatly improve the efficiency of safety detection of oil and gas pipelines. Combined with artificial intelligence and image processing technologies, it can intelligently identify and accurately classify pipeline defects. This report will compare the current state of development of related technologies and discuss pipeline inspection technologies.
Science Technology
Topic: Resource Scheduling Optimization for Large-Scale Refining and Chemical Production Processes
Speaker: Zhong Weimin
Professor and doctoral supervisor of East China University of Science and Technology, dean of the School of Information Science and Engineering, director of the Chemical and Engineering Society of China, and chairman of the Intelligent Manufacturing Committee of the Chemical and Engineering Society of China. He has long been engaged in the research of process modeling, control and optimization, industrial intelligence and intelligent systems. He has presided over more than 20 projects of the National Natural Science Foundation for Distinguished Young Scholars, national key research and development projects, sub-projects of national science and technology support projects and major scientific and technological development projects of enterprises, proposed and developed a series of methods, technologies, software and systems for intelligent manufacturing of energy and chemical processes, published more than 200 papers in international journals and conferences in the field of automation and chemical engineering, applied for more than 130 invention patents, registered more than 60 computer software copyrights, and worked in PTA, oil refining, ethylbenzene/styrene, polyethylene, Cement and other large-scale industrial equipment have been applied and demonstrated, and remarkable application results have been achieved. He has won 1 second prize of the National Science and Technology Progress Award, 4 first prizes of the Provincial and Ministerial Science and Technology Awards, and the Shanghai Youth Science and Technology Outstanding Contribution Award.
Summary of the report
As a pillar industry of the national economy, the refining and chemical industry is facing problems such as low resource utilization rate and high energy consumption, and is in urgent need of green and low-carbon process innovation and digital transformation. In view of the difficulties in optimization and control caused by the high complexity of the large-scale refining and chemical production process, the poor decision-making robustness caused by strong uncertainty, and the poor real-time optimization caused by centralized scheduling, this report combines artificial intelligence algorithms and operations research optimization methods to develop a series of efficient and low-carbon resource allocation modeling and optimization methods, production scheduling optimization methods considering uncertainty and multi-regional distribution collaborative scheduling optimization methods, so as to improve the decision-making quality of the refining and chemical production process and ensure the high efficiency and low-carbon production process.
Science Technology
Topic: Progress and Challenges of Intelligent Process Industry
Speaker: Ding Jinliang
Professor and doctoral supervisor of Northeastern University. Changjiang Scholar Distinguished Professor, winner of the National Science Fund for Distinguished Young Scholars, is currently the Dean of the School of Future Technology and the Deputy Director of the State Key Laboratory of Integrated Automation for Process Industries. He has presided over and participated in more than 30 scientific research projects such as the National Key R&D Program and the National Natural Science Foundation of China. He has published more than 200 papers, obtained more than 50 invention patents and 20 computer software copyrights. He has won the 14th China Youth Science and Technology Award, 1 second prize of the National Technological Invention Award (ranked 2nd) and 4 first prizes of the provincial and ministerial level. He is a member of the two technical committees of IFAC MMM and LSC, a senior member of IEEE, an executive director of the Chinese Society of Automation, a deputy director of the Process Control Committee, an editorial board member of the international journals IEEE TEVC, TETCI, TCAS II, and an associate editor of Control Engineering.
Summary of the report
The deep integration of artificial intelligence and manufacturing is triggering far-reaching industrial transformation. The process manufacturing industry occupies a fundamental strategic position in the national economy, intelligent manufacturing is an inevitable choice to improve its competitiveness, and how to realize the intelligence of the process manufacturing industry has put forward new challenges and opportunities for automation. This report focuses on the latest advances in research and scientific challenges in the field of process industry intelligence.
Science Technology
Theme: Spark Model Empowers New Industrialization
Speaker: Liu Cong
Vice President and Dean of the Research Institute of iFLYTEK, Deputy Director of the National Engineering Research Center for Speech and Language Information Processing, Part-time PhD Supervisor of the University of Science and Technology of China, National Leading Talent, Fellow of the Chinese Society of Artificial Intelligence, Standing Director of the Chinese Institute of Electronics, Vice Chairman of the Chinese Human Robot 100 Association, Distinguished Member of the China Computer Federation, and Founding Member of CTO Club. Mainly engaged in the research of speech language and computer vision and other technologies, he has established and led an AI R&D team of more than 1,500 people and achieved a number of innovative technologies and application achievements, leading the completion of the "iFLYTEK Xinghuo Cognitive Model" to support the company's application of multi-scenario products such as education and office. He has presided over a number of national, provincial and ministerial scientific research works such as the major project of scientific and technological innovation 2030-"new generation artificial intelligence". He has won three first prizes of provincial and ministerial science and technology progress awards, Anhui Youth May Fourth Medal, MIT TR35 China "Pioneer", CCF Outstanding Engineer and other honors.
Summary of the report
The "intelligent emergence" of cognitive intelligence large models has promoted the leap of AI technology, and also triggered a wave of development of large models at home and abroad. With the successive launch of GPT-4V, GPT-4 Turbo, Sora, etc., the construction of multi-modal large models and large model ecosystems has attracted more and more attention.
This report focuses on the latest effect of the V3.5 version of the iFLYTEK Xinghuo model and its continuous empowerment of product applications on the "N" track of education, medical care, industry, robotics, etc., which focuses on the application of the Xinghuo model in the industrialization fields such as code, industrial Internet and automobiles, and discusses how the large model can focus on the development of new industrialization.
Science Technology
Topic: Field-level Industrial Deterministic Networks for Smart Manufacturing: Mechanism Design and Practice
Speaker: Chen Cailian
Distinguished Professor of the Department of Automation, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Secretary of the General Party Branch of the École des Excellence des Études des École des Études des Excellence des Études des Études des Excellence in Paris, and National Outstanding He is mainly engaged in the research of comprehensive design theory and technology of industrial Internet perception, transmission and control. He has presided over more than 20 key R&D projects of the Ministry of Science and Technology and NSFC key projects, published more than 100 SCI papers, authorized more than 50 invention patents in China/the United States, and invented industrial Internet of Things gateways and other products have been applied in steel manufacturing and electronic manufacturing production lines. The research results have won 1 second prize of the National Natural Science Award (ranked 3rd), 3 first prizes of the Provincial and Ministerial Awards, 1 first prize of CAA Technological Invention Award, won the 2022 IEEE TCCPS Industrial Technology Excellence Award, and were selected as the "2022 Global Top Ten Computer Network and Communication Academic Stars" by N2Women and the China Young Female Scientist Award.
Summary of the report
The Industrial Internet of Things has gradually penetrated into the industrial site, promoting the gradual integration of IT and OT, forming a field-level industrial network system, which is the symbol of the new generation of industrial automation architecture and operation mode. This report will take the field-level industrial network system in intelligent manufacturing as the object, based on the field-level industrial wired/wireless converged network, and design the real-time reliable determination transmission mechanism of heterogeneous data for the transmission requirements of distributed dynamic perception and feedback control. In this paper, an association feature learning mechanism and a flow sequence association diagram method are proposed to realize the on-demand transmission of large-scale heterogeneous traffic, reduce the network transmission delay and jitter, and improve the resource utilization efficiency. The time-sensitive network (TSN) gateway equipment, testbed and configuration software to ensure heterogeneous data transmission performance have been developed, and a digital twin system supporting real-time interaction between production lines and networks has been constructed, realizing flexible configuration and dynamic networking of communication equipment, and providing key infrastructure for improving the perception-control collaboration of field-level industrial network systems.
Science Technology
Topic: Theory and Application of Knowledge and Data-Driven Network Swarm Intelligence
Speaker: Yu Wenwu
Chief Professor (Level 2), Doctoral Supervisor, Dean of the School of Mathematics, Selected as Changjiang Scholar of the Ministry of Education, Chief Scientist of the Key R&D Program of the Ministry of Science and Technology, Member of the Academic Committee of Southeast University, Executive Deputy Director of Jiangsu National Center for Applied Mathematics (Southeast University), He has published more than 100 IEEE Transactions articles, cited 20,000 times, and 30 ESI highly cited papers, and won 1 second prize of the National Natural Science Award, 2 first prizes of the Provincial Science and Technology Award/Natural Science Award, and 1 first prize of the National Science and Technology Award. Member of the editorial board of Systems, Man, and Cybernetics: Systems, Chinese Journal of Scientific Information Science, Acta Automatica Sinica, Systems Science and Mathematics, etc.
Summary of the report
This report begins with a brief review of intelligent unmanned systems in artificial intelligence and extends to generalized network swarm intelligence. Then, this report introduces the recent progress from the basic theories of reinforcement learning, causal prediction, and generative identification in collaborative learning of network swarm intelligence, and further elaborates on the future work and challenges on this basis. Then, it focuses on the new challenges faced by collaborative learning based on network swarm intelligence in the era of unmanned systems, smart grids, intelligent transportation, smart cities, big data and artificial intelligence 2.0, and then explores some thoughts on autonomous collaboration and game on this basis.
Science Technology
Topic: Data + AI Empowers New Industrial Operational Excellence
Speaker: Luan Xiaoli
Professor and doctoral supervisor of the School of Internet of Things Engineering, Jiangnan University. He has been engaged in the research of complex industrial process modeling, advanced control and optimization, industrial big data analysis and application, data mining and machine learning for a long time, and has published more than 160 SCI papers in journals such as Automatica, IEEE TAC, IEEE TIE, etc., and has authorized 66 domestic invention patents and 4 international invention patents. He has presided over more than 1,000 enterprise technology development projects, and won the first prize of scientific and technological progress of China Federation of Commerce, the first prize of scientific and technological progress of China Petroleum and Chemical Automation Application Association, and the second prize of scientific and technological progress of China Light Industry Federation. As the project leader, he has successively undertaken the National Natural Science Foundation of China for Outstanding Young Scholars, the National Natural Science Foundation of China, the key research and development projects of the Ministry of Science and Technology, the general projects of the National Natural Science Foundation of China, and the Youth Fund projects.
Summary of the report
In the new industry, various equipment and systems generate a large amount of real-time data, especially near-infrared spectroscopy data, which obtains molecular-level information with finer temporal and spatial granularity through continuous measurement at the microscopic level, so that the characterization of production process characteristics enters the microscopic field. Furthermore, by combining data and AI, a dynamic characterization method of process mode is proposed that can better reflect the essence of process operation, and the production operation is upgraded from process variable-based to process-based mode, which effectively realizes the integrated monitoring of production and operation safety and stability, process operation and benefit optimization, and provides strong support for new industrial operational excellence.
Science Technology
Panelist: Wu Yuanqing
Professor, Ph.D. supervisor, National Key R&D Program "Industrial Software" Key Special Special Overall Expert Group, National Key R&D Program "Intelligent Robot" Chief Scientist, National Excellent Youth (19 years), National Key Project Leader of the National Foundation Committee, Leader of Guangdong Outstanding Youth Team, Guangdong Outstanding Youth, Guangdong Young Pearl River Scholar, Deputy Editor-in-Chief of International Journal of Robust and Nonlinear Control. His research interests include industrial software, multi-robot systems, artificial intelligence, etc. He has presided over 9 national, provincial, ministerial and municipal projects, published more than 70 SCI journal papers, including 3 TAC (2 long articles), 2 Automatica (1 long article), and published 2 English monographs (Springer Press), applied for 44 invention patents, and authorized 20 patents.
Science Technology
Panelist: Wu Xiaolong
Associate professor of Beijing University of Technology, he has won the Outstanding Doctoral Dissertation Award of the Chinese Association of Automation, the first prize of the China Automation Science and Technology Progress Award, the first prize of the Entrepreneurship Award of the China Association of Inventions× the first prize of the Innovation Award, the Best Paper Award of the 2019 ICCSS International Conference, the Beijing Outstanding Graduate and other honors, and was selected as the "Young Talent Lifting Project of the Beijing Association for Science and Technology" in 2021.
He is currently a member of the Youth Working Committee of the Chinese Society of Automation, a member of the China Environmental Perception and Protection Automation Committee, and a reviewer for IEEE Transactions on Cybernetics, International Journal of Fuzzy Systems, Control Theory and Applications, Control Engineering, etc. He has published more than 30 academic papers in domestic and foreign journals and conferences, authorized more than 20 American/national invention patents, participated in the writing of 2 monographs, and participated in the compilation of 1 group standard and 2 industry standards.
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Topics and guests of the roundtable dialogue
Conversation topics
Moderator: Han Honggui, Professor, Beijing University of Technology
Topic: Opportunities and Challenges of Intelligent Manufacturing and New Industrialization
Panelist: Zhong Weimin, Professor, East China University of Science and Technology
Ding Jinliang is a professor at Northeastern University
Chen Cailian is a professor at Shanghai Jiao Tong University
Yu Wenwu is a professor at Southeast University
Wu Yuanqing is a professor at Guangdong University of Technology
Wu Xiaolong is an associate professor at Beijing University of Technology
Science Technology
Special Forum on Intelligent Manufacturing and New Industrialization
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