Yihuang Kang
Papers
2
Total Citations
10
H-Index
2
About
Yihuang Kang is a researcher whose work bridges human-robot interaction (HRI), educational technology, and machine learning. His key research areas include modeling HRI research trends, understanding student learning intentions in robotic programming, and applying data-driven methods to analyze complex human-robot systems. Kang’s major contributions include developing a machine learning approach that uses topic modeling to analyze over a decade of HRI research (2010–2021), revealing five dominant research factors such as handover dynamics. This work, cited 7 times, provides a systematic, data-backed framework for tracking the evolution of HRI. Additionally, his study on students’ intentions in learning visual robotic programming integrates the IS Success Model with utilitarian and hedonic values, offering insights into how perceived usefulness and enjoyment drive educational engagement in robotics. Though his citation counts are modest, Kang’s work stands out for its innovative use of ML to synthesize large-scale research landscapes and its practical implications for designing more effective HRI curricula. His achievements demonstrate a commitment to making HRI research more accessible and actionable for educators and technologists alike.
Research Focus
Key Achievements
Top Papers
- 1A Machine Learning Approach to Model HRI Research Trends in 2010~20217 citations · 2022
- 2