Marie-Luce Bourguet

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About

Marie-Luce Bourguet is a pioneering researcher at the intersection of human-robot interaction and educational technology, whose work is shaping the future of socially aware robotic tutors. Her primary research areas include affective computing, social robotics in education, and computer vision for human behavior analysis. Bourguet’s major contribution lies in developing systems that enable robots to perceive and respond to students’ emotional and behavioral states in real-time. Her most cited work, "Social Robots that can Sense and Improve Student Engagement" (2020, 18 citations), establishes a framework for tutor robots to detect disengagement and adapt their interactions, a critical step toward making robotic assistants effective in classrooms. She further demonstrated this capability in "The Impact of a Social Robot Public Speaker on Audience Attention" (2020, 8 citations), exploring how robots can maintain audience focus during remote lectures. Her foundational paper, "A Visual Sensing Platform for Robot Teachers" (2019, 6 citations), introduces a multi-student behavior recognition system that detects actions like "listening," providing the perceptual backbone for her later work. Bourguet’s research is notable for its practical focus on real-world deployment, addressing the challenge of creating robots that are not just tools but empathetic partners in learning. Her work has significant implications for distance education and personalized tutoring, positioning her as a key innovator in the emerging field of robot-assisted pedagogy.