My research aims to build embodied spatial intelligence systems that enable robots to perceive their surroundings, maintain persistent spatial memory, predict the consequences of actions, and acquire robust skills for long-horizon interaction. This research integrates spatial perception, embodied foundation models, robot policy learning, and the co-design of robot bodies and sensing systems.
I completed my master's and PhD at Peking University and the Technical University of Munich, where I worked on nonlinear least-squares optimization and Geometric Computer Vision.
I am actively recruiting motivated students and researchers to join the Embodied Spatial AI Lab at HKUST(GZ). Openings are available for MPhil students, research assistants, and interns starting in Fall 2026, and for PhD students starting in Spring/Fall 2027.
Join the LabGeometry-aware perception systems that enable robots to localize, map, and understand complex real-world environments through spatially consistent representations.
Persistent 3D and 4D world models that support long-horizon robot autonomy through geometry-centric tracking, reconstruction, and structured scene representations.
Learning-based robot systems that connect perception, representation, and reasoning with decision-making and interaction in dynamic environments.
I am actively recruiting PhD and MPhil students, research assistants, and interns to join the EmSAIL Group at HKUST(GZ). My research focuses on VLA, Imitation learning, Reinforcement learning, SLAM, 3D/4D scene representation, and Scene understanding.
Students are encouraged to contact me with their CV and research interests.
Self-motivation, curiosity, strong execution, and the ability to connect solid theoretical understanding with real-world robotic systems.