Papers
2
Total Citations
6
H-Index
2
About
Chi-Ho Lee’s research lies at the intersection of evolutionary computation, neural network design, and intelligent control systems, with a particular focus on robotics and ubiquitous computing. His most cited work, “Evolutionary Ordered Neural Network and its Application to Robot Manipulator Control” (2002), introduces a novel one-dimensional linked list encoding scheme for neural network architectures, where the order of neurons is critical for effective genetic operations. This evolutionary approach enables automated optimization of network topology, offering a powerful tool for adaptive robot manipulator control. In a subsequent study, “Evolutionary Generation of Artificial Creature’s Personality for Ubiquitous Services” (2007), Lee extends evolutionary methods to the domain of artificial life, demonstrating how personality traits can be evolved to enhance user interaction in pervasive computing environments. Though his citation counts are modest, Lee’s work represents early, creative contributions to evolutionary neural design and embodied AI, anticipating later trends in neuroevolution and personalized robotics. His research is particularly valuable for students exploring how evolutionary algorithms can shape both the structure and behavior of intelligent systems.
Research Focus
Key Achievements
Top Papers
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