Xingting Wu
Papers
1
Total Citations
14
H-Index
1
About
Xingting Wu is a leading researcher at the intersection of human-robot interaction, social robotics, and privacy ethics. Her work critically examines how the design characteristics of social robots—such as appearance, autonomy, and interactivity—influence users’ privacy concerns, a rapidly growing area of inquiry as robots become integrated into homes and public spaces. In her highly influential 2024 study, Wu employed a mixed-method approach combining PLS-SEM and fuzzy-set Qualitative Comparative Analysis (fsQCA) to uncover complex, non-linear relationships between robot design and user trust. This work, already garnering 14 citations within its first year, provides actionable insights for engineers and policymakers aiming to create socially acceptable robots without compromising user privacy. Wu’s contributions are notable for bridging quantitative modeling with configurational analysis, offering a nuanced understanding of how design trade-offs affect adoption. Her research is essential reading for students and scholars in human-robot interaction, design ethics, and technology acceptance, positioning her as a key voice in the responsible development of socially embodied AI.
Research Focus
Key Achievements
Top Papers
- 1