Yixuan Zhou

Papers

Total Citations

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About

Yixuan Zhou is a leading researcher in human-robot interaction (HRI), with a particular focus on adaptive collaboration in unstructured, real-world environments. Their most influential work, "Human-Robot Interaction in Museum Exhibition Assembly: A Framework for Adaptive Collaboration" (2025), addresses a critical gap in HRI by moving beyond structured industrial settings to tackle the unpredictable challenges of museum spaces. Zhou’s framework enables robots to dynamically interpret and respond to human actions during the assembly of complex exhibitions, bridging the gap between abstract curatorial concepts and tangible physical installations. This contribution has already garnered attention, with the paper cited once in its early publication, signaling growing impact in the field. Zhou’s work is notable for its practical application in cultural heritage and public engagement, demonstrating how robots can collaborate safely and effectively with humans in creative, non-repetitive tasks. By pioneering adaptive collaboration frameworks for museum environments, Zhou is shaping the future of HRI in contexts that demand flexibility, creativity, and real-time coordination—an achievement that holds promise for broader applications in education, art, and public spaces.