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About

Zahra Zahedi is an AI and robotics researcher whose work sits at the intersection of human-robot interaction, trust modeling, and explainable AI. Her research centers on a fundamental challenge in collaborative robotics: how can robots earn, maintain, and appropriately respond to human trust over time? Zahedi's most influential contribution is her development of trust-aware planning frameworks, which model how trust evolves dynamically during longitudinal human-robot teamwork. Her 2023 paper on this topic has garnered 12 citations, reflecting growing interest in building robots that treat trust not as a static given but as an active responsibility to cultivate. Complementing this, her game-theoretic models of trust explore the strategic interplay between human monitoring behavior and robot performance — recognizing that supervisory humans make calculated decisions about when and how closely to observe robotic teammates. More recently, Zahedi has extended her work into explainability, exploring how robots can deploy excuses alongside plan explanations to make their reasoning more actionable and accessible to everyday users. Collectively, her research addresses a pressing need in human-robot teaming: designing robotic systems that are not merely technically capable, but socially intelligent, transparent, and trustworthy partners in collaborative settings.