Yongsheng Ou, Professor

Dalian University of Technology, China

Biography: Ou Yongsheng, professor in Dalian University of Technology. In 2011, he received the support of the 100 Talents Program of the Chinese Academy of Sciences, and was selected into the National "Ten Thousand Talents Program" in 2020. Experts of the 13th Five-Year Key Intelligent Robot Group of the Ministry of Science and Technology, key project evaluation expert of Natural Science Fund Committee, and evaluation expert of national Science and Technology Award plan. He has undertaken many national projects, such as key projects of the National Natural Science Foundation of China, national major research plan projects, and the 863 project of the Ministry of Science and Technology. With the interdisciplinary background of robotics and intelligent control, in the past five years, he has published more than 180 EI / SCI papers in the field of artificial intelligence and robotics. He has cited 5047 times and published more than 30 articles in JCR 1, Google H-index 55. He led the team to develop a number of core key technologies and realize the transformation. The low-cost navigation technology developed by him is used for the new product Xinluo sweeping robot developed by Shenzhen Silver Star Intelligent Company, and the humanoid service robot of Shenzhen UBTECH Technology Co., Ltd. His research won the 2016 Wu Wenjun Artificial Intelligence Technology Progress Award (ranked first), the 2018 Shenzhen Municipal Science and Technology Progress Award (ranked first), and the 2020 Guangdong Provincial Technology Invention Award (ranked first).

Speech Title: Research on the Complex Skill Learning Method of Embodied Intelligence Robots

Abstract: At present, there is still a big gap between robots and humans in terms of mechanism, perception and control, and it is difficult for robots to adapt to changing scenes or tasks. In contrast, humans are better at handling missing, contradictory, and vague information. Therefore, integrating with human beings and the environment is an important means to solve the problem of insufficient robot intelligence. For complex scenarios, in-depth exploration of robot theory and practical problems under the situation of "human-in-loop", and robot multi-mode perception, knowledge reasoning, accurate and compliant control and other methods are studied. The main research contents include: (1) human operation intention understanding and behavior prediction in dynamic unstructured environment;(2) efficient migration and generalization technology of robot collaboration skills driven by knowledge reasoning; and (3) Human-machine collaborative compliance force control based on multi-mode information fusion.

Yu Rong, Professor

Guangdong University of Technology, China

Biography: Prof. Yu Rong is currently a distinguished professor and a doctoral supervisor at Guangdong University of Technology. He is also the recipient of the National Natural Science Foundation Outstanding Youth Award. His main research interests are Artificial Intelligence, Edge Computing, and the Internet of Things, with applications in fields like intelligent transportation, smart grid, smart home, and intelligent medical treatment. He has led over 20 scientific research projects, including those funded by the National Natural Science Foundation of China and major key projects of Guangdong Province's science and technology plan. He has published over 150 academic papers in prestigious journals and conferences, with his work receiving more than 13,000 citations on Google Scholar. He holds over 50 authorized invention patents and has taken the lead in formulating two national standards that have been officially promulgated. He has trained over 40 postgraduate and doctoral students, and his outstanding graduates have been honored with titles such as "National 100 Excellent Graduate Party Members" and "Star of Self-Improvement of Chinese College Students".

Zhijia Zhao, Professor

Guangzhou University, China

Biography: Zhijia Zhao is a Professor and Vice Dean of the School of Mechanical and Electrical Engineering at Guangzhou University, China, and serves as a Ph.D. Supervisor. He has been selected for the National High-Level Talent Program for Young Professionals (Young Top-notch Talent) and the Guangdong Special Support Program as a Young Pearl River Scholar. His research interests include robot control, intelligent control, and autonomous intelligent unmanned systems. In recent years, he has led more than ten national and provincial research projects. He has published over 100 SCI-indexed journal papers and has been granted more than ten invention patents. He received the Second Prize of the Guangdong Provincial Natural Science Award in 2023 (ranked first) and the Guangdong Youth Science and Technology Innovation Award in 2025. He has also been listed among the World's Top 2% Scientists in the Annual Scientific Impact Rankings released by Stanford University from 2019 to 2025. He currently serves as the Deputy Secretary-General of the 9th Youth Working Committee of the Chinese Association of Automation. He is also a member of the Early Career Advisory Board of the IEEE/CAA Journal of Automatica Sinica and serves as an Associate Editor for several prestigious journals, including IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Neural Networks and Learning Systems, and IEEE Transactions on Systems, Man, and Cybernetics: Systems.