Tian-Hao Yang
Papers
3
Total Citations
43
H-Index
3
About
Tian-Hao Yang is a researcher advancing the frontier of human-robot interaction through affective touch recognition. His work centers on enabling social robots to perceive and interpret human touch gestures and the emotions they convey—a critical capability for natural, empathetic communication between humans and machines. Yang’s major contributions include pioneering the use of decomposed spatiotemporal convolutions for touch gesture and emotion recognition, a method that efficiently captures both spatial and temporal dynamics of touch. His most cited paper (23 citations) established this foundational approach, while his subsequent work introduced multiscale spatiotemporal convolutions with attention mechanisms, achieving multitask recognition of both gesture and emotion simultaneously. To address the practical challenge of individual differences across users, Yang developed MASS, a multisource domain adaptation network that enables cross-subject touch gesture recognition without requiring per-user retraining. His research is notable for its direct application to socially assistive robots and embodied telecommunication, where reliable touch perception is essential. With a focused publication record from 2022, Yang’s work is quickly gaining traction, demonstrating the growing importance of tactile communication in next-generation human-robot interaction systems.
Research Focus
Key Achievements
Top Papers
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