Yu-Liang Weng
Papers
1
Total Citations
7
H-Index
1
About
Yu-Liang Weng is a forward-thinking researcher whose work bridges human-robot interaction (HRI) and machine learning, with a focus on modeling and predicting research trends. His most-cited study, "A Machine Learning Approach to Model HRI Research Trends in 2010~2021" (2022, 7 citations), demonstrates his innovative use of topic modeling to analyze a vast corpus of HRI literature, identifying five dominant research factors—including handover dynamics—that have shaped the field over a decade. This work not only provides a data-driven roadmap for future HRI studies but also showcases Weng’s skill in applying ML techniques to synthesize complex research landscapes. His contributions are particularly valuable for students and researchers seeking to understand the evolution of HRI, as his model offers a clear, quantitative perspective on emerging trends. Weng’s ability to distill large-scale data into actionable insights marks him as a rising voice in computational social science and robotics. With a growing citation footprint, his work is poised to influence how researchers navigate and prioritize HRI challenges, making him a key figure to watch in the intersection of machine learning and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1A Machine Learning Approach to Model HRI Research Trends in 2010~20217 citations · 2022