Dalian University of Technology, China
Jingsong Li, male, born in 1987, received the Ph.D. degree from the Hebei University of Technology, Tianjin, China, in 2017, and became a Postdoctoral Fellow with Tsinghua University, Beijing, China, during 2017-2019, all in electrical engineering. He is currently an associate professor in Dalian University of Technology, Dalian, China. His research interests include Energy Storage Transformer, Submarine Cable Detection, magnetic losses characteristics modeling and measurement analysis and application of magnetic materials in electrical engineering, and analysis of high-frequency electromagnetic vibration and noise characteristics of electrical equipment. He was selected as Outstanding Young Scientific and Technological Talents of Liaoning Province in 2022. Focusing on the major national demand for large-scale energy storage and advanced manufacturing of intelligent equipment in multi-application scenarios and multi-objective planning in the new energy power system, he is committed to the research and development of theories, technologies, software and hardware systems for electrical equipment performance evolution, load matching, energy conservation and consumption reduction, and have presided over or completed more than 10 projects (topics) such as the National Natural Science Foundation of China, China Postdoctoral Science Fund, provincial (ministerial), municipal and enterprise cooperation projects. Over the past five years, the total amount of funding has reached more than ¥13 million. He has published more than 20 relevant academic papers, 8 authorized national patents (including 3 invention patents), 6 invited reports at international (domestic) academic conferences, participated in the formulation of 2 industry standards, and 1 unique technology application has been gradually put into the market.
A. Prof. Qiushi Cui
Chongqing University, China
Dr. Qiushi Cui, Vice Chair of Web Forum Task Force, Big Data Analytics Committee, IEEE Power and Energy Society, and Founding Chair of Big Data Mentoring Forum Series. He graduated from Illinois Institute of Technology (IIT) and McGill University (McGill) in 2012 and 2017, respectively, and has worked as R&D engineer and postdoctoral researcher at Opal Real Time Simulation (OPAL-RT) in Canada and Arizona State University (ASU) in USA. His research is closely integrated with artificial intelligence, big data, power system and new energy grid integration, and his main research interests include power system artificial intelligence, power system protection and control, integrated energy system, electric vehicle grid integration, and grid real-time simulation and modeling.
Prof. Xiaomin Kang,
University of South China, China
He achieved his bachelor and Ph.D degree in Material Sciecne and Engineering, Southwest Jiaotong University in 2011 and 2017, respectively. After graduation, he further served as a postdoctor and research fellow in Prof. Luo Jinglli’s group (Fellow of the Canadian Academay of Engineering) to fulfil his job in the research of next generation energy conversion and storage devices, with an emphasis on exploring the oxygen evolution/reduction reaction and electrochemical carbon dioxide conversion at room temperatures. In 2022, he worked as an Associated Professor in School of Mechanical Engineering, South China University. Till now, He is hosting a National Natural Science Foundation of China, Shenzhen Postdoctral innovatiove research progam, respectively. As a core-participant, he is a member in Shenzhen Innovative Research Team Program: Hydrogen energy and fuel cell electrocatalytic materials and Innovative project of Shenzhen graphene manufacturing innovation center: Development of graphene based materials for anti-corrosion and antifouling of marine equipment and facilities, respectively. Besides, he once hosted a China Postocroral Science Foundation in 2019. Till now, he has published over 15 papers and 4 patents in Chemical Communication, Polymer Chemistry, Journal of Material Chemistry A, Journal of Alloys and Compounds, etc.