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About

Yuhua Liang is a leading researcher at the intersection of human-robot interaction (HRI), persuasive technology, and trust communication. Her work fundamentally explores how robots can influence human behavior through strategic verbal and social mechanisms, drawing from established principles of human persuasion. Liang’s most impactful contribution is her widely cited study on public fear of autonomous robots and AI (194 citations), which provides critical, nationally representative data on societal anxieties—a foundational resource for the field. She has also pioneered the application of classic persuasion tactics in robotics, demonstrating that robots can effectively use verbal reciprocity and the "foot-in-the-door" sequential-request strategy to increase compliance. Her research advances a communication-based model of trust, examining how both user-generated and robot-generated messages dynamically shape human-robot trust and interaction outcomes. By grounding HRI in robust communication theory, Liang’s work offers essential insights for designing more effective, trustworthy, and socially intelligent robots, with notable applications in inclusive education. Her contributions are vital for understanding the psychological and communicative dynamics that will define our future with autonomous agents.