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About

Tianyang Yue is an emerging researcher specializing in human-robot interaction (HRI), with a particular focus on in-vehicle robotics, robot transparency, and emotional communication design. His work sits at the intersection of interaction design, automotive intelligence, and cognitive ergonomics, addressing how robots can communicate more effectively and safely with human users. Yue's most influential contribution, "Robot Transparency and Anthropomorphic Attribute Effects on Human–Robot Interactions" (2021, 18 citations), examines how anthropomorphic design and transparent communication strategies shape user trust and experience. Complementing this, his work on abstract emotional expression (13 citations) explores how facial expression design in virtual interfaces can enhance the emotional intelligence of smart products. His research on proactive in-vehicle robot interaction (11 citations) applies transparency theory to real-world driving contexts, optimizing how robots convey information across voice and visual channels. His multimodal warning systems study (10 citations) further demonstrates a commitment to driving safety through thoughtful interaction design. Collectively, Yue's research contributes meaningfully to safer, more intuitive human-robot experiences in automotive environments — a domain of growing importance as autonomous and semi-autonomous vehicles become increasingly prevalent. His work is particularly valuable for designers and engineers developing next-generation intelligent vehicle systems.