Maosong Yan
Papers
1
Total Citations
12
H-Index
1
About
Maosong Yan is a leading researcher in affective computing and human-computer interaction, with a specific focus on emotion recognition using physiological signals. His work addresses the fundamental challenge of accurately classifying human emotional states from multimodal data, a task complicated by the diversity of emotional expression and individual physiological differences. Yan's most notable contribution is the development of a multi-attention-based neural network for emotion classification, which integrates signals from multiple physiological modalities—such as electrodermal activity and heart rate—to achieve superior performance. This work, published in 2024, has already garnered 12 citations, reflecting its immediate impact and relevance in the field. By advancing deep learning architectures tailored for noisy, heterogeneous physiological data, Yan is paving the way for more robust and naturalistic human-robot and human-computer interactions. His research holds promise for applications in mental health monitoring, adaptive user interfaces, and empathetic robotics, making him a rising figure to watch in the intersection of machine learning and psychophysiology.
Research Focus
Key Achievements
Top Papers
- 1