Jaeryoung Lee
Papers
29
Total Citations
604
H-Index
12
About
Jaeryoung Lee is a pioneering researcher at the intersection of social robotics, autism therapy, and human-robot interaction, whose work has profoundly shaped how intelligent robots are designed to support children with Autism Spectrum Disorder (ASD). With over 480 cumulative citations, Lee's research tackles one of the most challenging frontiers in assistive technology: enabling robots to autonomously recognize, respond to, and sustain the engagement of children with atypical behavioral expressions. Her landmark 2017 cross-cultural study on measuring engagement in robot-assisted autism therapy (128 citations) established foundational methods for evaluating therapeutic effectiveness, while her deep learning framework CultureNet (83 citations) demonstrated how AI can decode nuanced engagement signals from children's facial expressions. Beyond clinical applications, Lee has been instrumental in advancing the concept of culturally competent robotics, arguing compellingly that assistive robots must respect and adapt to cultural differences in human behavior — a position that shaped the international CARESSES EU-Japan project. Her investigations into robot design features, temperature perception during physical interaction, and physiological emotion sensing through EDA reveal a researcher committed to understanding the full human experience of robot therapy, ultimately making these technologies more empathetic, effective, and globally inclusive.
Research Focus
Key Achievements
Top Papers
- 1Measuring Engagement in Robot-Assisted Autism Therapy: A Cross-Cultural Study128 citations · 2017
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- 4Paving the way for culturally competent robots: A position paper62 citations · 2017
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- 6NAO-Dance Therapy for Children with ASD29 citations · 2017
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- 9The CARESSES EU-Japan Project: Making Assistive Robots Culturally Competent15 citations · 2019
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