Nael Jaber

Rafik Hariri University

Papers

2

Total Citations

7

H-Index

2

About

Nael Jaber is a robotics and computer vision researcher whose work bridges autonomous systems and environmental monitoring. His research focuses on developing intelligent robotic platforms for infrastructure inspection and ecological surveillance, leveraging deep learning and multi-modal sensing. Jaber’s most impactful contribution is the Deep-Pest-Detector system, which combines aerial drones with RGB and thermal imagery to automatically detect and geo-locate processionary moth nests on pine trees. This work, cited 4 times, integrates a custom deep neural network with a Kalman filter for precise GPS-based nest mapping, offering a scalable solution for pest management in forestry. Additionally, his design of a windmill climbing robot addresses the hazardous task of turbine maintenance, proposing a robotic mechanism to reduce human risk in the growing wind energy sector. Though early in his career, Jaber’s work demonstrates a clear trajectory toward practical, high-impact applications of robotics in agriculture and renewable energy, showcasing how autonomous systems can solve real-world environmental and industrial challenges.

Research Focus

Key Achievements

2
H-Index
2
Papers
7
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Deep-Pest-Detector: Automated Detection and Localization of Processionary Moth Nests on Pine Trees via Aerial Drones and Deep Neural Networks
4 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Rafik Hariri University

Top Papers

  1. 1
  2. 2
    Windmill Climbing Robot
    3 citations · 2018

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago