Henry Powell
Papers
5
Total Citations
55
H-Index
5
About
Henry Powell is a pioneering researcher at the intersection of social robotics and human-robot interaction (HRI), whose work fundamentally explores how robots can forge meaningful social bonds with people. His primary research areas include the psychology of commitment in HRI, adaptive robotic teaching, and the application of deep learning to infer subjective human states. Powell’s major contribution lies in demonstrating that a robot’s perceived effort—such as adapting its teaching pace or persisting through difficulties—can elicit a genuine sense of commitment from human partners, leading to increased patience and cooperation. His seminal 2019 paper, “Feeling committed to a robot,” (18 citations) lays the theoretical groundwork for this phenomenon, while his 2019 follow-up (17 citations) provides experimental evidence. Powell has also shown that an “adaptive robot teacher” can significantly boost a human’s learning performance (6 citations), and his 2022 work (8 citations) pioneers the use of deep learning to non-invasively detect subjective self-disclosure during interactions. By blending cognitive science with robotics, Powell is helping to design robots that are not just tools, but trusted partners in education, therapy, and collaborative tasks.
Research Focus
Key Achievements
Top Papers
- 1Feeling committed to a robot: why, what, when and how?18 citations · 2019
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