Arjun Sharma

Khalifa University of Science and Technology

Papers

1

Total Citations

4

H-Index

1

About

Dr. Arjun Sharma is a leading researcher in industrial automation and safety systems, with a primary focus on autonomous inspection technologies for critical energy infrastructure. His most-cited work, "Autonomous Inspection System for Anomaly Detection in Natural Gas Pipelines" (2020, 4 citations), introduces a novel framework that integrates robotics and machine learning to enhance the routine monitoring of pipeline networks. This contribution directly addresses the oil and gas industry's stringent safety standards by enabling real-time detection of structural anomalies, reducing human risk and operational downtime. Dr. Sharma’s research bridges the gap between theoretical control systems and practical field deployment, offering scalable solutions for predictive maintenance. His work has been recognized for its potential to transform legacy inspection protocols into intelligent, autonomous processes. By combining sensor fusion with anomaly detection algorithms, he has laid the groundwork for safer, more efficient pipeline operations. Dr. Sharma continues to advance the field of industrial cyber-physical systems, with ongoing projects exploring adaptive inspection strategies for hazardous environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Autonomous Inspection System for Anomaly Detection in Natural Gas Pipelines
4 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Khalifa University of Science and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago