Ellie Mamantov

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About

Ellie Mamantov is a pioneering researcher at the intersection of human-robot interaction, social navigation, and mental health robotics. Her work focuses on designing robots that communicate effectively and support human well-being. In her most-cited paper, "Observer-Aware Legibility for Social Navigation" (2022, 13 citations), Mamantov introduced a novel method for creating navigation paths that simultaneously signal a robot’s goal while remaining visible to a specific observer—addressing a critical gap in prior legible motion research that ignored observers’ limited field of view. This contribution enhances robot transparency and trust in shared spaces. Mamantov also explores robots as therapeutic tools, as seen in "Deep Breathing Phase Classification with a Social Robot for Mental Health" (2023, 5 citations), where she developed a system for robots to guide and classify deep breathing exercises, a proven intervention for anxiety. Her recent work, "Breathe Easy" (2025, 2 citations), extends this to pediatric care, using robots to reduce stress during oral challenges. By combining technical innovation with compassionate application, Mamantov is shaping a future where robots are both legible companions and accessible mental health aids.