Speakers

Prof.Hongzhi Wang

Harbin Institute of Technology, China

Hongzhi Wang, Professor, PHD supervisor, the head of massive data computing center and the vice dean of the honors school of Harbin Institute of Technology, the secretary general of ACM SIGMOD China, outstanding CCF member, a standing committee member CCF databases and a member of CCF big data committee. Research Fields include big data management and analysis, database systems, knowledge engineering and data quality. 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. He also serves as a member of ACM Data Science Task Force. He has won First natural science prize of Heilongjiang Province, MOE technological First award, Microsoft Fellowship, IBM PHD Fellowship and Chinese excellent database engineer. His publications include over 300 papers in the journals and conferences such as VLDB Journal, IEEE TKDE, VLDB, SIGMOD, ICDE and SIGIR, 6 books and 6 book chapters. His PHD thesis was elected to be outstanding PHD dissertation of CCF and Harbin Institute of Technology. He severs as the reviewer of more than 20 international journal including VLDB Journal, IEEE TKDE, and PC members of over 50 international conferences including SIGMOD, VLDB, KDD, ICML, NeurpIS, ICDE, etc. His papers were cited more than 3500 times. 

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. 

Prof. Weishan Zhang

China University of Petroleum (East China), China

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.

Assoc. Prof. Zongwei Luo

Beijing Normal University, China

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.

Senior Engineer Shiling Zhang

State Grid Chongqing Electric Power Company Chongqing Electric Power Research Institute, China

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. 

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.