Yaqian Zhao
Papers
1
Total Citations
41
H-Index
1
About
Dr. Yaqian Zhao is a leading researcher in affective computing and human-robot interaction, with a focus on emotion recognition in conversational contexts. Her most-cited work, "Hierarchically stacked graph convolution for emotion recognition in conversation" (2023, 41 citations), introduces a novel graph-based framework that models both self-dependencies and inter-speaker dynamics within dialogues. This approach significantly enhances the accuracy of emotion detection, enabling robots to better interpret human affective intentions and respond empathetically during interactions. Dr. Zhao’s contributions advance the integration of graph neural networks into conversational AI, bridging the gap between computational models and natural human communication. Her research has implications for developing socially intelligent robots capable of nuanced emotional engagement. With a growing citation impact, Dr. Zhao is recognized for pushing the boundaries of how machines understand and mirror human emotions, making her work essential for students and researchers exploring emotion-aware systems, graph-based learning, or human-robot collaboration.
Research Focus
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Top Papers
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