Max Robotics — Global Service Robot Directory + US Certification

About

Chung-Yeon Lee is a leading researcher at the intersection of robotics, deep learning, and human-aware artificial intelligence. His work focuses on enabling intelligent mobile robots—particularly social-service and domestic robots—to perceive, learn from, and safely interact with humans in dynamic, real-world environments. Lee’s major contributions include pioneering dual-memory deep learning architectures for lifelong learning of everyday human behaviors (34 citations), which allow robots to continuously adapt without forgetting prior knowledge. He also developed a multimodal anomaly detection system using deep auto-encoders for object slip perception in mobile manipulation robots (18 citations), addressing critical reliability challenges in noisy sensor environments. His visual perception framework for intelligent mobile robots (17 citations) integrates state-of-the-art deep learning to enhance safe human-robot interaction. Lee’s impact extends beyond publications: his team won the RoboCup@Home 2021 Domestic Standard Platform League, demonstrating the real-world effectiveness of his perception-action-learning systems. With a focus on modular, robust software architectures for home service robots, Lee’s work is shaping the next generation of autonomous, socially-aware robotic assistants.