Longxiang Gao

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About

Longxiang Gao is a leading researcher at the intersection of autonomous systems, digital twins, and robotic intelligence. His work focuses on bridging the gap between physical and virtual environments to overcome hardware limitations in intelligent systems. Gao’s most influential contribution is the “Internet of Digital Twin” framework, which integrates digital twin technology with IoT to enhance the computational and decision-making capabilities of smart vehicles and robotic arms. This foundational work, published in 2025, has already garnered 16 citations, reflecting its rapid impact on the field. He also advances autonomous vehicular networks through a ROS-based collaborative driving framework, optimizing data transmission for safer, more efficient vehicle coordination. In robotics, Gao tackles the complex challenge of bimanual manipulation with his spatial-temporal graph diffusion policy, which combines kinematic modeling with imitation learning to predict precise end-effector poses. His work is notable for its practical orientation—applying cutting-edge AI and middleware solutions to real-world systems. With a growing citation record and contributions that span theory and application, Gao is shaping the future of intelligent, autonomous physical systems.