Chin-Kun Yang
Papers
1
Total Citations
6
H-Index
1
About
Chin-Kun Yang is a leading researcher at the intersection of artificial intelligence, the Internet of Things (IoT), and smart robotics, with a particular focus on educational technology. His most cited work, "Evaluation of the Established IoT Smart Home Robot Teaching Module Based on Embedded Thematic-Approach Strategy" (2020, 6 citations), exemplifies his core contribution: designing and validating innovative teaching modules that integrate AI-driven smart home robots into STEM curricula. By embedding thematic learning strategies with IoT, big data, and machine learning technologies, Yang has pioneered methods to enhance human work efficiency through intelligent robotic systems. His research demonstrates how neural networks and expert systems can be practically applied to create adaptive, real-world learning environments. Yang’s work is notable for bridging the gap between advanced AI concepts and accessible educational tools, offering a replicable model for project-based learning in robotics. With a growing citation footprint, his studies are increasingly referenced by educators and engineers seeking to cultivate hands-on AI literacy. Yang’s achievements underscore his commitment to transforming theoretical AI into tangible, efficiency-boosting applications for the smart home and classroom alike.
Research Focus
Key Achievements
Top Papers
- 1