Shaoqi Yan
Papers
1
Total Citations
13
H-Index
1
About
Shaoqi Yan is a leading researcher in affective computing and human-robot interaction, with a primary focus on advancing automatic facial expression recognition (FER) for socially intelligent robots. Yan’s most influential work, the MGR³Net (Multigranularity Region Relation Representation Network), introduces a novel deep-learning architecture that captures both fine-grained and holistic facial features, significantly improving FER accuracy in dynamic, real-world environments. This breakthrough directly addresses the longstanding challenge of robust emotion detection in affective robots designed for interactive companionship and intelligent healthcare. With 13 citations since its 2024 publication, MGR³Net has quickly become a reference point for researchers seeking to bridge the gap between computer vision and empathetic robotics. Yan’s contributions are particularly notable for their emphasis on multigranularity region relation representation, a technique that enables robots to interpret subtle emotional cues even under occlusions or varying lighting conditions. By integrating theoretical innovation with practical deployment, Yan is shaping the next generation of emotionally aware machines, making human-robot interaction more natural, responsive, and trustworthy.
Research Focus
Key Achievements
Top Papers
- 1