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About

Fares Abawi is a robotics and artificial intelligence researcher whose work sits at the intersection of human-robot interaction (HRI), social cognition, and multimodal machine learning. With a growing body of work accumulating over 50 citations, Abawi has made meaningful contributions to understanding how robots can be designed to engage more naturally and effectively with humans. His early research explored how robot personality shapes user acceptance, demonstrating through a dice game scenario that socially engaged robotic behavior fosters greater human trust. He has since advanced the field by developing humanoid robots capable of crossmodal social attention — enabling them to resolve conflicting sensory inputs much as humans do — and investigating how facial expressions and gaze influence collaborative human-robot dynamics. Complementing this social focus, Abawi has also pursued biologically inspired visuomotor architectures, enabling robots to identify, localize, and grasp objects through end-to-end neural learning. His more recent contributions include Wrapyfi, a practical middleware integration tool streamlining multi-robot communication, and an innovative simulation framework that reduces reliance on human participants in HRI studies. Together, these efforts reflect a researcher committed to building robots that are not only technically capable, but genuinely socially intelligent.