- Computer Science Division
- Associate Professor
- Web site
- Courses - Undergraduate
- Algorithm and Data Structure, Java programming, Software Engineering, C programming
- Courses - Graduate
- Computational Intelligence, Soft Computing
- Educational Background, Biography
- Sep., 2006, Software College, Northeastern University, China, Bachelor of Engineering.
Mar. 2009, Software College, Northeastern University, China, Master of Engineering.
2006-2011, Neusoft (China), Alpine electronics R&D Europe GmbH (Germany), Software Engineer.
Mar. 2014, Graduate School of Design, Kyushu University, Japan, Doctor of Engineering.
Apr. 2014, the University of Aizu, Assistant Professor.
Apr. 2016, the University of Aizu, Associate Professor.
- Current Research Theme
-  Fitness Landscape of Evolutionary Computation<br> Interactive Evolutionary Computation<br> Chaos and Chaotic Evolution<br> Fusion of Game Theory and Evolutionary Computation<br> Machine Learning<br> Software Engineering
- Key Topic
- Computational Intelligence, Neural Network, Fuzzy System, Evolutionary Computation, Chaos, Machine Learning, Software Engineering
- Affiliated Academic Society
- IEEE, Japanese Society for Evolutionary Computation
- Hiking, Tennis
- School days' Dream
- To become a professor at university
- Current Dream
- To become a man of value
- Try not to become a man of success, but rather to become a man of value. (Albert Einstein)
- Favorite Books
- "Analects" （Lunyu) by Confucius
- Messages for Students
- Please do your best in the University of Aizu!
- Publications other than one's areas of specialization
- Establishing theoretical fundamental of algorithmic mechanism design for evolutionary computation
We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This research is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.