Jiang Xu

Northeastern University, Tongji University

Papers

Total Citations

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About

Jiang Xu is a researcher whose work sits at the critical intersection of autonomous systems and neuroengineering. His key research areas include multi-sensor data fusion for autonomous systems and next-generation neurotechnologies for motor rehabilitation. Xu’s major contribution lies in addressing the fundamental challenge of temporal synchronization in sensor fusion—his 2022 paper on worst-case time disparity analysis of message synchronization in ROS (21 citations) provides a rigorous framework for ensuring that data from multiple sensors are sampled at sufficiently close time points, a prerequisite for accurate perception in autonomous vehicles and robots. This work has direct implications for improving the reliability of real-world autonomous systems. More recently, Xu has ventured into neuroengineering, as evidenced by his 2025 paper on motor primitive models for restoring natural human movement (3 citations). This forward-looking work explores how advances in AI and neuroprosthetics can enable more intuitive rehabilitation interventions, bridging the gap between robotic systems and human neural control. With a growing citation footprint and a trajectory spanning both practical robotics and cutting-edge neurotechnology, Xu is establishing himself as a versatile researcher tackling foundational problems in autonomous perception and human-machine interaction.