Hanjing Huang
Papers
3
Total Citations
32
H-Index
2
About
Hanjing Huang investigates the intersection of human-robot interaction, decision-making, and communication design. Their work explores how robot attributes—such as perceived ability, language use, and feedback framing—influence human behavior in high-stakes and risky contexts. In their most-cited study (22 citations), Huang examined how robot capability, task complexity, and risk jointly shape whether people follow a robot’s advice, revealing nuanced dynamics in human trust and reliance on automated systems. A subsequent study (9 citations) applied the Computers are Social Actors paradigm and the foreign language effect to show that bilingual individuals respond differently to robot feedback depending on the language used, highlighting cultural and linguistic factors in human-robot communication. Huang’s 2023 work further demonstrated that both robot language and attribute framing can alter people’s risk-taking tendencies. By integrating psychological theory with robotics, Huang advances our understanding of how to design more effective, context-aware robot advisors. Their research is particularly relevant for developers of assistive and collaborative robots, as well as scholars studying trust, persuasion, and human-automation interaction.
Research Focus
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Top Papers
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