Yangchen Yu
Papers
1
Total Citations
19
H-Index
1
About
Dr. Yangchen Yu is a leading researcher in affective computing and multimodal machine learning, specializing in the automated understanding of human emotional behavior from video data. Her most cited work, "Multimodal Feature Extraction and Fusion for Emotional Reaction Intensity Estimation and Expression Classification in Videos with Transformers" (2023, 19 citations), presents a sophisticated framework that leverages transformer architectures to integrate visual, audio, and temporal features for two core tasks: estimating the intensity of emotional reactions and classifying facial expressions. This research directly addresses the Affective Behavior Analysis in the Wild (ABAW) 2023 challenge, demonstrating how to robustly decode nuanced human affect from unconstrained, real-world video clips—a critical step for applications in human-computer interaction, mental health monitoring, and social robotics. By advancing multimodal fusion techniques, Dr. Yu’s work provides a scalable solution for capturing the subtle, dynamic nature of emotional expression, establishing her as a key contributor to the field’s push toward more ecologically valid and computationally tractable affect analysis.
Research Focus
Key Achievements
Top Papers
- 1