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About

Chengji Wang is an emerging researcher specializing in human-robot interaction (HRI), with a particular focus on in-vehicle robotics, robot transparency, and emotional communication design. Their work sits at the intersection of interaction design, cognitive ergonomics, and intelligent systems, addressing how robots can communicate more effectively and safely with human users. Wang's most notable contributions explore how anthropomorphic attributes and transparency influence the quality of human-robot relationships. Their 2021 study on robot transparency and anthropomorphism (18 citations) demonstrated that carefully calibrated robot communication characteristics can meaningfully improve user experiences and task performance. Complementing this, their research on abstract emotional expression design (13 citations) advances our understanding of how virtual facial expressions on intelligent interfaces can be optimized for intuitive human comprehension. Particularly impactful is Wang's focused body of work on in-vehicle robots, examining how proactive transparency-driven interactions (11 citations) and multimodal warning systems (10 citations) can enhance driving safety without introducing additional cognitive burdens. This research carries real-world significance as autonomous and semi-autonomous vehicles become increasingly prevalent. Collectively, Wang's growing citation record reflects meaningful influence in shaping safer, more intuitive human-robot interaction frameworks for next-generation intelligent environments.