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About

Jin Joo Lee is a pioneering researcher in human-robot interaction, specializing in socially assistive robots that enhance children's learning and social development. Her work bridges artificial intelligence, affective computing, and developmental psychology to create robots capable of understanding and responding to human nonverbal cues. Lee's most influential contribution is the development of computational models that predict interpersonal trust and engagement by analyzing nonverbal signals—a breakthrough demonstrated in her 2013 paper (95 citations), where her model outperformed human accuracy in assessing trustworthiness. Her 2016 study on affective personalization of a social robot tutor for children's second language skills (306 citations) remains a landmark, showing how robots can modulate students' emotional states to rival one-to-one tutoring effectiveness. Lee also led the creation of Tega, an expressive Android-based social robot platform (37 citations), and conducted extended classroom deployments with DragonBot to teach nutrition through play (124 citations). Her 2017 work on backchannel opportunity prediction (19 citations) advanced robots' ability to engage children as active listeners. With over 1,000 total citations, Lee's research has fundamentally shaped how robots can serve as empathetic, adaptive learning companions in real-world educational settings.