Zakria Qadir

University of Technology Sydney

Papers

1

Total Citations

20

H-Index

1

About

Zakria Qadir is a leading researcher at the intersection of artificial intelligence, renewable energy, and robotics, with a primary focus on enhancing the operational efficiency of solar photovoltaic systems. His most cited work, "Deep Learning-Based Recognition and Classification of Soiled Photovoltaic Modules Using HALCON Software for Solar Cleaning Robots" (2025, 20 citations), tackles a critical bottleneck in solar energy: the efficiency loss caused by dust and debris accumulation on panels. By integrating deep learning with industrial machine vision, Qadir developed a robust classification system that enables autonomous cleaning robots to accurately identify and prioritize soiled modules, directly improving energy output and reducing maintenance costs. This contribution exemplifies his broader impact in applying intelligent systems to real-world sustainability challenges. With a growing citation record, Qadir’s work is shaping the future of smart solar farms and autonomous maintenance. His research not only advances computer vision and robotics but also provides scalable, data-driven solutions for the global transition to cleaner energy.

Research Focus

Key Achievements

1
H-Index
1
Papers
20
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
Deep Learning-Based Recognition and Classification of Soiled Photovoltaic Modules Using HALCON Software for Solar Cleaning Robots
20 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Technology Sydney

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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