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About

Quan Dong Nguyen is a robotics researcher whose work sits at the intersection of humanoid locomotion, manipulation, and medical robotics. His primary research areas include dynamic loco-manipulation, model predictive control (MPC), and reinforcement learning for legged systems, with a notable sideline in dental robotics. Nguyen’s major contributions include the development of a kinodynamic pose optimization framework that enables humanoid robots to push heavy objects while maintaining balance, and a RL-augmented MPC system that allows legged robots to adaptively balance and reflect their swing foot to navigate complex terrains without entrapment. His most cited work, “Kinodynamic Pose Optimization for Humanoid Loco-Manipulation” (10 citations), exemplifies his approach to combining dynamics and control for real-world tasks. He also co-authored a visionary paper on a femtosecond laser-enabled intraoral dental robotic device, showcasing his interdisciplinary reach. Nguyen’s work on the HECTOR humanoid platform and co-optimization of arm and leg design for quadrupedal robots further underscores his impact in advancing dynamic, synchronized loco-manipulation. With a growing citation footprint, Nguyen is shaping the future of autonomous, adaptive robots for both industrial and medical applications.