Kuo-Wei Lin
Papers
1
Total Citations
7
H-Index
1
About
Kuo-Wei Lin is a researcher whose work bridges computational neuroscience and intelligent transportation systems, with a particular focus on bio-inspired traffic signal control. His most cited paper, "Matsuoka Neuronal Oscillator for Traffic Signal Control Using Agent-based Simulation" (2013, 7 citations), introduces a novel application of the Matsuoka neuronal oscillator—a model of central pattern generators (CPGs) originally developed for humanoid robotics—to manage traffic signals at isolated four-phase intersections. This interdisciplinary contribution demonstrates how neural dynamics can optimize urban mobility, offering an alternative to traditional traffic control methods. Lin’s work highlights the potential of leveraging biological principles for engineering solutions, showcasing his ability to translate complex neural models into practical, agent-based simulations. While his citation count reflects a niche but impactful area, his research stands out for its creativity in applying CPG concepts beyond robotics, opening new avenues for adaptive traffic management. Lin’s achievement lies in pioneering a cross-domain approach that inspires further exploration of neuromorphic control in smart city infrastructure.
Research Focus
Key Achievements
Top Papers
- 1