Xinjie Qiu
Papers
2
Total Citations
53
H-Index
2
About
Dr. Xinjie Qiu is a leading researcher in the intersection of underwater robotics and deep learning, with a primary focus on automated infrastructure inspection and biofouling management. Her most influential work, "Research on the identification and distribution of biofouling using underwater cleaning robot based on deep learning" (2023, 42 citations), pioneered a novel approach that integrates convolutional neural networks with robotic cleaning systems to map and classify marine growth on submerged structures—a critical advancement for maintaining hydropower and maritime assets. Building on this, her 2024 study on automatic detection of expansion joints in dam stilling pools (11 citations) demonstrates a robust, real-time solution for identifying structural vulnerabilities in challenging underwater environments. Dr. Qiu’s contributions are notable for bridging the gap between computer vision and practical robotics, enabling autonomous systems to perform tasks that traditionally required hazardous human diving. Her work has immediate applications in dam safety, offshore energy, and environmental monitoring, and her citation trajectory reflects growing recognition among civil and mechanical engineers. By combining deep learning with robotic autonomy, Dr. Qiu is shaping the future of intelligent underwater inspection and maintenance.
Research Focus
Key Achievements
Top Papers
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- 2