Cameron D. Hassall
Papers
2
Total Citations
24
H-Index
2
About
Cameron D. Hassall’s research lies at the intersection of cognitive neuroscience, human-robot interaction, and social learning, exploring how the brain monitors feedback and adapts behavior in dynamic social contexts. His most cited work, “A win-win situation: Does familiarity with a social robot modulate feedback monitoring and learning?” (2021, 20 citations), investigates how social species, including humans, modulate neural feedback-monitoring when interacting with robots versus humans. Hassall demonstrates that when strangers receive rewards, feedback-monitoring is attenuated—suggesting that less value is assigned to outcomes for unfamiliar others. This finding has profound implications for understanding social cognition and designing more intuitive human-robot interfaces. By bridging social neuroscience and robotics, Hassall’s research illuminates how familiarity shapes learning and reward processing, with applications in education, therapy, and collaborative AI. His work is widely cited in fields ranging from social neuroscience to human-computer interaction, reflecting its interdisciplinary impact. Hassall’s contributions offer a compelling window into how our brains navigate the increasingly social world of machines.
Research Focus
Key Achievements
Top Papers
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- 2