Gnanathusharan Rajendran
Papers
10
Total Citations
143
H-Index
7
About
Gnanathusharan Rajendran is a leading researcher at the intersection of social robotics, autism, and human-robot trust. His work primarily explores how robots can understand and simulate human social cognition—particularly Theory of Mind (ToM)—to improve human-robot collaboration. Rajendran has made foundational contributions to measuring trust in human-robot interaction, developing new psychometric tools like the Propensity to Trust scale using innovative Delphi methods (cited 35 times). His research on child-robot interaction, especially with autistic children, investigates how gaze and joint attention can be leveraged for social skills training. Notably, his case study on gesture deficits in autism (25 citations) and his work on designing expressive robot faces and trust repair strategies after repeated failures have shaped how robots can maintain long-term social relationships. With over 140 combined citations across his top papers, Rajendran’s interdisciplinary approach—bridging psychology, robotics, and human-computer interaction—has advanced both the theoretical understanding of trust and the practical design of socially intelligent robots for education and therapy.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Toward Improved Child–Robot Interaction by Understanding Eye Movements22 citations · 2018
- 4Exploring Theory of Mind for Human-Robot Collaboration20 citations · 2022
- 5Do You Think I Approve of That? Designing Facial Expressions for a Robot10 citations · 2017
- 6
- 7Sensitivity of Trust Scales in the Face of Errors8 citations · 2022
- 8Cultural Social Signal Interplay with an Expressive Robot7 citations · 2018
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- 10