Papers
6
Total Citations
64
H-Index
5
About
Shiming Huang is a researcher specializing in human-robot interaction, educational robotics, and the psychological dimensions of artificial intelligence. Their work sits at a compelling crossroads between technology design and human behavior, with particular focus on how social robots influence learning, emotional well-being, and self-disclosure. Huang's most influential contribution examines robot-assisted mathematics tutoring, demonstrating that social robots can produce over one-third learning gain in multiplication and symbolic reasoning among schoolchildren — though notably revealing that learning outcomes vary meaningfully by gender, as shown in a landmark study using a Hanson Einstein robot with Chinese students. This nuanced finding challenges blanket assumptions about educational technology's universal effectiveness. Beyond the classroom, Huang has pioneered investigations into robots as social companions, finding that young people during the COVID-19 pandemic showed greater willingness to self-disclose to social robots than to social media — a striking result suggesting that perceived safety shapes human communication choices. Their theoretical work also critically examines the uncanny valley hypothesis and media equation frameworks, grounding abstract AI design principles in empirical testing. With a growing citation record across six key publications and a total of approximately 64 citations, Huang is an emerging voice reshaping how researchers and designers think about socially intelligent machines.
Research Focus
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