Papers

9

Total Citations

226

H-Index

7

About

Junsong Yuan is a leading researcher in human-robot interaction (HRI), social robotics, and multimodal perception, with a focus on enabling robots to understand and respond to natural human behavior. His major contributions include developing systems that allow robots to interpret upper body gestures, facial expressions, and human-object interactions from RGB-D video, as well as advancing robot hearing through robust sound-event classification using spectrogram texture features. Yuan’s work on non-iterative SLAM has also provided a lightweight framework for dense simultaneous localization and mapping, tailored for micro-robots. With over 200 citations across his most-cited papers—including 65 for his gesture-based HRI system and 54 for sound-event classification—his research has significantly impacted the fields of telepresence and multiparty interaction. Notably, he has explored context-aware interaction among virtual characters, robots, and humans, and has contributed to face and expression recognition. Yuan’s innovative fusion of sensor data and machine learning techniques makes his work essential for students and researchers interested in creating socially intelligent robots that seamlessly collaborate with people.

Research Focus

Key Achievements

7
H-Index
9
Papers
226
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
Human–Robot Interaction by Understanding Upper Body Gestures
65 citations · 2014
📈 Most Prolific Year: 2014 (3 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Nanyang Technological University, University at Buffalo, State University of New York

Top Papers

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    Non-iterative SLAM
    27 citations · 2017
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago