Papers
14
Total Citations
117
H-Index
6
About
Soheil Keshmiri is a researcher whose work bridges the seemingly disparate worlds of multi-robot systems and social neuroscience, united by a deep interest in interaction and embodiment. His early contributions established a centralized framework for multi-robot formation control (25 citations), addressing coordination and pursuit-evasion games. More recently, Keshmiri has pioneered the study of how physical embodiment—whether in robots or humans—affects brain activity, particularly in older adults. His 2021 paper on "shrunken social brains" (18 citations) challenges the classic social brain hypothesis by modeling how social interaction itself might reduce neural complexity. Using multiscale entropy, he has quantified how communication through humanoid robots, video chat, and in-person conversation differentially engage the prefrontal cortex (12 citations). His work also includes decoding perceived difficulty of spoken content from brain activity (6 citations) and classifying gentle versus strong touch (5 citations), with clear applications for conversational robot-assistive elderly care. By combining robotics, computational modeling, and cognitive neuroscience, Keshmiri offers a unique lens on how our brains adapt to—and are shaped by—the media and machines we interact with.
Research Focus
Key Achievements
Top Papers
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- 5Multi-robot, dynamic task allocation: a case study8 citations · 2013
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