Papers
6
Total Citations
338
H-Index
6
About
Huili Chen is a leading researcher at the intersection of child development, human-robot interaction, and family dynamics. Her work fundamentally reimagines social robots not just as solitary tutors for children, but as "conversational catalysts" that enhance long-term, high-quality human-human relationships within the home. Chen’s most impactful contribution, the 2020 study on reciprocal peer learning with a social robot (244 citations), demonstrated that robots can significantly boost children’s learning and emotional engagement. She has since pioneered the design of long-term parent-child-robot triadic interactions, moving beyond the dyadic child-robot paradigm to empower parents. Her research introduces dynamic robot role adaptation, integrating flow theory to sustain engagement in multi-person interactions. Chen also created the DAMI-P2C dataset, a critical resource for analyzing dyadic affect in parent-child multimodal communication. Her recent work explores how robots can serve as conversational catalysts, fostering more reciprocal and high-quality interactions between family members. By focusing on the social and emotional context of learning, Chen’s research provides a powerful framework for designing interactive technologies that strengthen family bonds and support children’s cognitive and social development in real-world home environments.
Research Focus
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