Sanghyub Lee
Papers
4
Total Citations
51
H-Index
3
About
Sanghyub Lee is a pioneering researcher at the intersection of child psychiatry, robotics, and artificial intelligence, whose work is transforming how we screen for neurodevelopmental disorders. His primary research focuses on developing non-invasive, game-based diagnostic tools for Attention Deficit Hyperactivity Disorder (ADHD) in children, leveraging deep learning and sensor technologies. Lee’s major contributions include creating a novel ADHD classification system using children’s skeleton data captured during interactive screening games, achieving 26 citations for his foundational 2022 work. He advanced this by introducing a three-tier classification model—distinguishing between normal, ADHD-risk, and ADHD groups—a significant improvement over traditional binary approaches, as highlighted in his 16-citation follow-up study. Lee also pioneered a multi-RGB-D sensor system that enhances classification accuracy through sophisticated feature selection, and extended his expertise to pathological gait recognition using mobile robots equipped with ultrawideband localization and depth cameras. His work is notable for replacing subjective observational methods with objective, data-driven screening, potentially enabling earlier intervention for millions of children worldwide. With a growing citation impact and a clear translational focus, Lee is establishing himself as a key innovator in AI-driven pediatric healthcare.
Research Focus
Key Achievements
Top Papers
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