Report Title: Neurodynamic Approaches to Distributed Optimization and Resource Allocation Problems
Presenter: Professor Qin Sitian, Doctoral Supervisor
Unit: Harbin Institute of Technology (Weihai)
Time: 10:00-11:00, Monday, May 26, 2025
Location: Room A321, School of Mathematics
Report Summary: This presentation focuses on neurodynamic approaches for distributed optimization and resource allocation problems, highlighting the recent research progress and representative achievements of our group in this area. The report begins with an overview of the problem background and research significance, emphasizing the broad application prospects of neurodynamic approaches in real-world systems. It then systematically summarizes our algorithmic designs and theoretical results for distributed optimization and resource allocation problems under various types of constraints, aiming to provide new modeling perspectives and methodological support for real-time solutions to such problems.
Biography of the Speaker:
Qin Sitian, a professor and doctoral supervisor, is the dean of the School of Science at Harbin Institute of Technology (Weihai) and a young expert of the Taishan Scholars Program in Shandong Province. The main research direction is neural dynamics optimization methods and their applications. More than 80 high-level SCI papers have been published, including over 20 in IEEE Transactions. Two monographs have been published with Science Press and Harbin Institute of Technology Press. In recent years, I have successively presided over four projects funded by the National Natural Science Foundation of China and one project funded by the China Postdoctoral Science Foundation. He has held important positions at over ten international authoritative academic conferences in this field, such as conference chairperson, conference procedure chairperson, and publication chairperson, and has been invited to conduct academic visits to The Chinese University of Hong Kong, The Hong Kong Polytechnic University, and City University of Hong Kong four times successively.