Speakers
Keynote Speaker 1 |
| Prof. Weishan Zhang China University of Petroleum (East China), China BIO: Weishan Zhang, professor of China University of Petroleum (East China). His main research directions are big data intelligent processing, artificial intelligence, etc. He is the director of Credible Intelligent Lab of Shandong Province. He has published more than 100 papers. Currently H index is 26, i10 index is 76. He is the PI/Co-PI of a number of projects such as the National Natural Science Foundation of China and the National Key R&D Program. For his research on federated intelligence, he won the first prize of Science and Technology Progress Award of Qingdao city, the second prize of Shandong Province Science and Technology Progress Award, the third prize of Wu Wenjun Artificial Intelligence Science and Technology Progress Award. Title: Credible Federated Intelligence: Exploration and Practice Abstract: Federated learning can collaboratively train AI models while protecting data privacy. In practical industry environment, Non-IID characteristics of data affect the effectiveness of federated learning. And also, security attacks may course serious problems. Therefore, credible federated intelligence is necessary. In this talk, a reinforcement learning based federated learning, and a hypernetwork based Federated Self-Learning (CFSL) will be discussed, where credible, personalized federated self-learning for Non-IID environment will be evaluted to show the effectiveness of credible federated intelligence. |
Keynote Speaker 2 |
| Assoc. Prof. Zongwei Luo Beijing Normal University, China BIO: Simon is an independent director and chief scientist of High Tech companies. After graduating from the University of Geirgia with a PhD in Computer Science and minorinbusiness, Simon has started to focus on industrial solutions with increasingly growing expertises in AI, Big Data and Industrial Internet. With more than 50 high quality publication in recent five years nd active successful industrial engagement, Simon is listed consecutively in 2021 & 2022 Stanford Top 2% World Scientists. Simon recently is electedas the secretary general of Guangdong AI Institute of Higer Education, engaging to develop service platform of excellence in the area of AI and Higer Education research, serving Guangdong and BigBayArea. Title: An Ethical Pespective of AI/LLM & Big Data Abstract: AI LLMs' recent performance over big data has caused great attention with considerable opportunities to be discovered and exploited. At the same, the unbelievable fsst recursive evolution and improvement has posed tremendous pressure upon ethics. In this speech we wil share the recent development of AI LLM and analyze its potential impact from ethical perspective. It is suggested that AI governance is becoming an essential capacity to gain advantages in global competition. |
Keynote Speaker 3 |
| Senior Engineer Shiling Zhang State Grid Chongqing Electric Power Company Chongqing Electric Power Research Institute, China BIO: Zhang Shiling, Senior engineer, Doctor of Engineering, is currently the director of Science and Technology management, physical and chemical testing technology, Electric Power Research Institute of State Grid Chongqing Electric Power Company. Long engaged in high voltage and insulation technology, physical and chemical testing technology research and production work. He is a full-time key researcher of State Grid Provincial Laboratory of Chongqing Electric Power Company and Key Provincial and ministerial Laboratory of Chongqing, member of IEEE Sub-Committee on New Sensing and Monitoring Technology, member of Insulation Materials and Insulation Technology Professional Committee of Chinese Society of Electrotechnical Engineering, member of high voltage Sub-committee of Chinese Society of Electrical Engineering. The development of UHV dry converter transformer bushing and SF6 gas insulation through-wall bushing have been applied to the construction of UHV AC/DC engineering. Presided over the completion of GIS fault detection sensor technology and system, won the Outstanding Innovation Achievement Award of the International Innovation and Entrepreneurship Expo, and awarded the title of Outstanding Scientist by Chongqing Society of Electrical Engineering. As the first author, he has published more than 90 SCI/EI retrieval papers in domestic and foreign journals and international top academic conferences, and 18 Chinese core journals of Peking University. His innovation achievements have won 9 provincial and ministerial awards, such as the first prize of Chongqing Science and Technology Progress Award and the special first prize of China Water Conservancy and Electric Power Quality Management Association, and accepted 1 international invention patent. He has authorized 20 national invention patents and utility models, 18 software Copyrights, more than 20 international and domestic conference reports, and presided over 2 provincial and ministerial projects of basic frontier and 3 science and technology projects of the headquarters of State Grid Corporation as the project leader. Title: Application of Information Fusion and Electro-thermal Decoupling Technology in Whole Life Cycle of High Voltage Power Equipment Abstract: Taking the converter transformer for UHV converter valve hall as the research object, this special speech discusses the construction process of its three-dimensional digital model from the insulation structure of the transformer body. Further, focusing on the outgoing device and bushing structure of converter transformer, this paper introduces the typical structure, the actual valve hall operation environment and the heating theoretical model of high-voltage power equipment under high harmonic load from the perspective of high-voltage power equipment operation, analyzes the electro-thermal coupling nonlinear electric field of transformer outgoing device, and optimizes its insulation structure by using RBF neural network and NSGA-II multi-objective optimization algorithm. Considering the complex structure of converter transformer and its outgoing line device and converter bushing area are important typical accessories, this paper focuses on the construction of digital twin 3D model in this area, and carries out on-site operation and maintenance simulation test and high current Functional response analysis under high voltage load. The digital twin model of the outlet device area is constructed according to the electro-thermal coupling physical field simulation model. The electro-thermal sensor is used to monitor the on-line voltage and current waveform in real time, and the interaction between the on-site operating parameters and the loading data of the digital twin model is realized. On the other hand, the intelligent extraction and identification of material area in the digital twin model is realized, and the material parameter performance can be changed according to the physical field environment, so as to adapt to the structural design and performance evaluation of different operating environments. Furthermore, in order to analyze the relationship between the internal transient temperature of the converter bushing and its short-time current carrying capacity and long-term aging performance, an evaluation process method of the long-term internal insulation performance of the high-voltage bushing is proposed. Focuses on the 3D construction of digital twin model in the outgoing area of converter transformer. Its research method can be extended to key components such as converter body winding structure, oil paper insulation area and on load switch. The research results of this paper can provide theoretical guidance and technical reference for the insulation structure design of converter transformer body, especially for the structural design and operation maintenance of outlet device area, and can provide some theoretical guidance for on-line analysis of short-term current carrying capacity and long-term aging performance of converter transformer outlet device area. |
Keynote Speaker 4 |
| Prof. Hongzhi Wang Harbin Institute of Technology, China BIO: Professor, PHD supervisor, the head of massive data computing center, the secretary general of ACM SIGMOD China, outstanding CCF member, IEEE Senior member, a standing committee member CCF databases and a member of CCF big data committee. He was “starring track” visiting professor at MSRA and postdoctoral fellow at University of California, Irvine. Prof. Wang has been PI for more than 10 national or international projects including NSFC key project, NSFC projects and National Technical support project, and co-PI for more than 10 national projects include 973 project, 863 project and NSFC key projects. Title: Time Series Data Processing: Foundation of IOT Abstract: IOT generates time series continuously. Thus, effectively time series data processing techniques forms the foundation of IOT, which also bring the challenges of strong co-relationship, continues data types and ordered time window. In this talk, I will introduce the applications of time series, the challenges of time series data processing as well as our research results in this area including time series database, various kinds of time series analytics algorithms and time series cleaning algorithms and systems. |
