Invited Speakers
Invited Speaker Ⅰ
Prof. Wei Song
Jiangnan University, China
Brief Introduction: Wei Song is a Professor and PhD Supervisor at Jiangnan University, IEEE Senior Member, IEEE CIS/SMCS Senior Member, and Vice Dean of the School of Artificial Intelligence and Computer Science. He has published over 100 papers in conferences and journals such as IEEE TNNLS, TEVC, TCYB, TSMC-S, TETCI, etc., and holds 12 authorized invention patents. His has achieved two First Prizes and one Second Prize in the Science and Technology Award from the China General Chamber of Commerce, the Rong Zhiquan Award, and the Sangma Award. He has served as a conference/communication reviewer for the National Natural Science Foundation of China (NSFC), the Ministry of Education Degree Center, and as a program committee member for several international conferences.
Speech Title: Learning-driven Evolutionary Search for Solving Dynamic Multiobjective Optimization Problems
Abstract: In dynamic optimization problems, environmental changes can be characterized as various dynamics and pose a challenge to dynamic optimization algorithms. However, existing swarm intelligence-based dynamic optimization algorithms mainly rely on some predetermined rules, limiting their capability in handling various dynamics. Additionally, diversity loss remains a critical issue behind the inefficiency of existing dynamic optimization algorithms. Consequently, maintaining high diversity in dynamic environments is essential for automatically addressing this challenge. Faced with these challenges, a series of neural network-assisted dynamic optimization algorithms are proposed. For dynamic optimization problems, we design a particle search control network to automatically determine the learning targets and accelerating coeffect for each individual in the population; For multi-objective optimization problems under diverse dynamics, we design a dynamic optimization algorithm based on a swarm behavior decision neural network and an efficient hidden node adjustment mechanism. These algorithms are capable of solving dynamic optimization and dynamic multi-objective optimization problems across various dynamics with very small time cost.
Invited Speaker Ⅱ
Assoc. Prof. Jiyu Cheng
Shandong University, China
Brief Introduction: Jiyu Cheng received the B.E. degree in automation from Shandong University, Jinan, China, in 2015 and the Ph.D. degree in department of electronic engineering from the Chinese University of Hong Kong, Hong Kong, in 2019. He is currently an Associate Research Professor with the Department of Control Science and Engineering, Shandong University. His current research interests include multirobot system, deep learning, and reinforcement learning.
Speech Title: Multirobot Autonomous Collaboration in Complex Scenarios
Abstract: Multirobot collaboration plays a vital role in many real-life applications, such as inspection, search and rescue and so on. As a main research branch in robotics, it has attracted wide attention and developed rapidly. However, efficient collaboration in especially large and unstructured environments is still a challenging problem. In this talk, we will introduce our recent research on several typical multirobot tasks and talk about our exploration on how the data driven approach can empower the collaboration in a multirobot system.
Invited Speaker Ⅲ
Prof. Xiaolin Qin
University of Chinese Academy of Sciences, China
Brief Introduction: Qin Xiaolin, Deputy Chief Engineer of Chengdu Institute of Computer Applications, Chinese Academy of Sciences (CAS), and Professor at the University of CAS (UCAS), PhD Supervisor, CCF and IEEE senior member. He is a recipient of the Tianfu Qingcheng Plan for Leading Talents in Scientific and Technological Innovation, a Provincial Academic and Technical Leader, a winner of the Sichuan Provincial Outstanding Youth Fund, a Tianfu Ten-Thousand Talents Plan Technology Elite, an Overseas High-Level Studied Talent, and a CAS Western Youth Scholar. He has presided over the National Natural Science Foundation of China, National Key R&D Program Projects, CAS STS Programs, and Major Science and Technology Projects of Sichuan Province in artificial intelligence. He has won awards such as the Provincial and Ministerial First Prize, Second Prize of Sichuan Provincial Science and Technology Progress, CAS President's Excellence Award, China Industry-University-Research Cooperation Innovation Award, and China Technology Market Association Golden Bridge Award. He serves as an evaluation expert for the National Science and Technology Progress Award and more than 10 provinces/municipalities including the Ministry of Science and Technology, Ministry of Education, Ministry of Industry and Information Technology, National Natural Science Foundation of China, and Sichuan Province.
Speech Title: Large Models Cross-domain Deep Perception: Algebraic Vision to Embodied Intelligence
Abstract: This report begins with discussions on Tesla FSD and Huawei ADS solutions, providing a concise introduction to large visual models and deep perception models, along with the challenges they face—particularly in cross-domain few-shot visual learning and embodied intelligence for robotics. It presents the team's advances in cross-domain deep perception, proposing a Cross-domain Fourier Boundary Feature Capture Network to mitigate excessive capture of deep semantic information through geometric structure regularization.