Xiaoyu Xing

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About

Xiaoyu Xing is a researcher at the forefront of intelligent spacecraft systems, specializing in the intersection of reinforcement learning and knowledge engineering for aerospace applications. Her most impactful work centers on developing advanced AI-driven methods for spacecraft fault diagnosis and autonomous repair. In her highly cited 2023 paper, Xing introduced an improved Deep Deterministic Policy Gradient (DDPG) algorithm to construct a performance-fault knowledge graph for spacecraft control systems. This innovation enables space robots to rapidly locate and rectify faults, significantly enhancing mission reliability. Her contributions bridge the gap between deep reinforcement learning and practical space operations, offering a scalable framework for autonomous anomaly resolution. With her work gaining traction in the aerospace AI community, Xing is establishing herself as a key voice in applying graph-based reasoning and adaptive control to next-generation space missions. Her research holds promise for reducing human intervention in orbital repairs and improving the resilience of complex spacecraft systems.