Danial Waleed

American University of Sharjah

Papers

1

Total Citations

72

H-Index

1

About

Dr. Danial Waleed is a leading figure in the field of robotic pipeline inspection and intelligent infrastructure monitoring, with a particular focus on leak detection systems for the oil and gas industry. His most impactful work, "An In-Pipe Leak Detection Robot With a Neural-Network-Based Leak Verification System" (2018, 72 citations), introduces a custom-designed inspection robot tailored for pipes of 0.203 meters in diameter—a common industrial standard. This robot integrates onboard pressure sensors with a neural network verification system, enabling highly accurate and automated leak detection. Dr. Waleed’s major contribution lies in bridging mechanical robotics with machine learning, creating a system that not only identifies leaks but reduces false positives through intelligent data analysis. His work has significant implications for reducing environmental hazards and maintenance costs in critical infrastructure. With 72 citations, this paper stands as a key reference in smart pipeline monitoring. Dr. Waleed’s research continues to advance the reliability and autonomy of industrial inspection systems, marking him as an innovator at the intersection of robotics and artificial intelligence.

Research Focus

Key Achievements

1
H-Index
1
Papers
72
Total Citations
72
Avg Citations/Paper
🏆 Most Cited Paper
An In-Pipe Leak Detection Robot With a Neural-Network-Based Leak Verification System
72 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: American University of Sharjah

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago