Ee Jing Loh
Papers
2
Total Citations
113
H-Index
2
About
Ee Jing Loh is a leading researcher in Human-Robot Interaction (HRI), specializing in the social and cognitive mechanisms that shape how people perceive and collaborate with robots. Her work fundamentally challenges the traditional HRI paradigm—where robots are always the helpers—by exploring scenarios where robots need human assistance. In her highly cited 2020 study (100 citations), Loh demonstrated how social-cognitive recovery strategies, such as apologies or explanations, can significantly boost a robot’s perceived likability, capability, and trustworthiness after errors. This research provides critical design guidelines for building resilient, socially intelligent robots. Her earlier 2016 work (13 citations) broke new ground by showing that a robot’s stated limitations—rather than its intentions—are more effective at prompting users to offer help. By reframing the robot as a vulnerable, assistance-seeking partner, Loh has opened new avenues for more balanced, cooperative human-robot teams. Her contributions are essential for developing robots that can gracefully recover from mistakes and proactively engage users in shared goals, advancing the field toward more natural and effective human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robot-stated limitations but not intentions promote user assistance13 citations · 2016