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About

Rebeca Marfil is a prominent researcher specializing in cognitive robotics, social human-robot interaction, and computer vision, whose work has significantly advanced our understanding of how robots can perceive, reason, and meaningfully engage with humans in real-world environments. Her research spans gesture recognition, audio-visual perception, and biologically inspired attention mechanisms, with early contributions including a real-time human motion analysis system and fast gesture recognition frameworks that laid important groundwork for natural human-robot communication. Marfil has made notable strides in social robotics architecture, particularly through her work on cognitive software frameworks and middleware solutions enabling high-performance robotic systems. Her deployment of autonomous robots in demanding real-world contexts — from museum exhibitions to geriatric care facilities — demonstrates a consistent commitment to translating theory into practice. Notably, her CLARC project and work on socially assistive robots for elderly care reflect a deeply humanistic research vision. With her most cited paper accumulating 43 citations and a body of work collectively exceeding 240 citations, Marfil's contributions have meaningfully shaped the fields of social and assistive robotics, making her an influential voice for researchers exploring the intersection of artificial intelligence, perception, and compassionate robot design.