Lianpeng Sun

Sun Yat-sen University

Papers

1

Total Citations

40

H-Index

1

About

Lianpeng Sun is a leading researcher at the intersection of artificial intelligence and environmental engineering, with a primary focus on leveraging deep learning for urban water infrastructure management. His most-cited work, "Deep learning-assisted automated sewage pipe defect detection for urban water environment management" (2023, 40 citations), introduces a transformative approach to automating the inspection of sewage systems. By applying advanced computer vision and neural network architectures, Sun’s research enables rapid, accurate identification of pipe defects—such as cracks, blockages, and corrosion—that are critical to preventing environmental contamination and costly urban flooding. This contribution directly addresses a pressing global challenge: aging water infrastructure and the need for efficient, data-driven maintenance. Sun’s work stands out for its practical impact, offering a scalable solution that reduces reliance on manual inspection, which is often slow, hazardous, and error-prone. His findings have been widely cited by peers in civil engineering, environmental science, and AI, underscoring their interdisciplinary significance. Through this pioneering integration of deep learning with environmental monitoring, Lianpeng Sun is helping to shape smarter, more resilient cities for the future.

Research Focus

Key Achievements

1
H-Index
1
Papers
40
Total Citations
40
Avg Citations/Paper
🏆 Most Cited Paper
Deep learning-assisted automated sewage pipe defect detection for urban water environment management
40 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Sun Yat-sen University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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