Thi Le Quyen Dang

Japan Advanced Institute of Science and Technology

Papers

Total Citations

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About

Thi Le Quyen Dang is a pioneering researcher at the intersection of human-robot interaction (HRI), affective computing, and cross-cultural robotics. Her work fundamentally explores how robots can develop socially appropriate emotional behaviors by integrating cultural context, memory retrieval, and human-inspired social mechanisms. Dang’s key contributions include modeling robot emotion representation that accounts for cultural differences—a critical step toward robots that can interact naturally with users from diverse backgrounds. Her 2017 paper “Encoding cultures in robot emotion representation” (12 citations) demonstrates how cultural norms influence emotional and behavioral responses in HRI, proposing that robot emotions should adapt to their user’s cultural context. She further advanced this field by modeling social referencing and social sharing processes, enabling robots to learn emotional responses through memory retrieval and human guidance. Though her citation counts are modest, Dang’s work addresses a fundamental challenge in socially assistive robotics: creating robots that can build trust through culturally-aware, human-like emotional expression. Her research lays essential groundwork for developing robots capable of long-term, meaningful social relationships with humans across different cultural settings.