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About

Mayada Oudah is a leading researcher in human-robot interaction (HRI) and machine behavior, focusing on how intelligent systems can learn to cooperate with people in dynamic, real-world settings. Her work bridges artificial intelligence and social psychology, addressing two fundamental challenges: enabling robots to adapt online during repeated interactions with human partners, and understanding how people perceive robot minds. Oudah’s most cited paper, “Learning to Interact with a Human Partner” (2015, 19 citations), tackles the critical problem of online learning in HRI, highlighting the limitations of random exploration in mutual adaptation. Her 2024 study, “Perception of experience influences altruism and perception of agency influences trust in human–machine interactions” (18 citations), reveals how humans attribute experience and agency to robots, directly shaping altruistic behavior and trust—insights essential for designing socially acceptable AI. In “Confronting barriers to human-robot cooperation” (2020, 12 citations), she systematically explores the trade-off between efficiency and risk in cooperative machine behavior. Through rigorous experiments involving human-human, robot-robot, and human-robot interactions, Oudah has established herself as a key voice in creating more intuitive, trustworthy, and adaptive robotic partners.