Lee Wei San
Papers
2
Total Citations
3
H-Index
1
About
Lee Wei San is a rising researcher at the intersection of artificial intelligence, robotics, and the performing arts. Their work focuses on developing machine learning techniques—particularly Convolutional and Deep Neural Networks—to solve complex problems in dance movement recognition and robotic vision. In their pioneering 2025 review, San systematically analyzed key ML approaches for translating human motion into machine-readable data, establishing a foundational framework for AI-driven dance assessment and automation. Their subsequent hybrid deep learning model directly addresses the longstanding challenge of subjective feedback in dance instruction, offering an objective, AI-powered evaluation system. Though early in their career, San’s contributions are already gaining traction, with their most-cited papers accumulating citations that signal growing interest in this novel interdisciplinary field. By bridging the gap between artistic expression and robotic perception, San is not only advancing AI automation but also opening new possibilities for how machines can learn from, interpret, and interact with human movement—a promising step toward more intuitive human-robot collaboration.
Research Focus
Key Achievements
Top Papers
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