Congratulations to our PhD student Wu Lin for successfully passing his PhD oral defense
Oct 2024
Lin Wu's doctoral defense focused on the research topic "Towards Adaptive Knowledge Transfer in Evolutionary Transfer Optimization." During his postgraduate studies, Lin Wu was devoted to studying and designing adaptive knowledge transfer methods to intelligently address the challenges of transferring knowledge across tasks, including determining what to transfer, how to transfer, and when to transfer in various transfer optimization scenarios. His innovative achievements include:
1. Designing a fuzzy classifier-assisted method to decide what to transfer across tasks adaptively. By training the fuzzy classifier to measure the usefulness of candidate source tasks to the target task, the proposed method effectively addresses the issue of what to transfer in evolutionary sequential transfer optimization.
2. Designing a domain adaptation ensemble method to decide how to transfer across tasks adaptively. By combining the strengths of multiple complementary domain adaptation approaches, the proposed method effectively addresses the issue of how to transfer in evolutionary multitasking optimization.
3. Designing a fuzzy logic-based method to decide when and how to transfer across tasks adaptively. By utilizing the capability of fuzzy logic in modeling and reasoning with imprecise information, the proposed method effectively addresses the issues of when to transfer and how to transfer in evolutionary multitasking optimization.
Lin Wu received his B.E. degree from Hubei University of Technology, Wuhan, China, in 2017 and his M.S. degree from Shenzhen University, Shenzhen, China, in 2020. His research interests include evolutionary computation, transfer optimization, and related applications. He has published several papers in prestigious research journals, contributing significantly to evolutionary optimization.
Dr. Lin Wu will join Shenzhen University as a Postdoctoral Fellow, where he will continue his research in evolutionary transfer optimization and related applications. We wish him a successful and enriching postdoctoral journey ahead!