Ahmed Zekry

Queen's University

Papers

1

Total Citations

7

H-Index

1

About

Ahmed Zekry is a leading researcher in autonomous navigation and multi-sensor fusion, with a focus on developing robust systems for complex urban environments. His most cited work, "The NavINST Dataset for Multi-Sensor Autonomous Navigation" (2025, 7 citations), represents a significant contribution to the field by providing a comprehensive, real-world dataset that captures diverse lighting conditions, including challenging indoor garage scenarios with dense 3D maps. This dataset, developed at the Navigation and Instrumentation (NavINST) Laboratory, integrates data from multiple commercial sensors, enabling researchers to benchmark and advance algorithms for localization, mapping, and perception. Zekry’s work addresses critical gaps in autonomous systems, particularly in environments where traditional GPS-based navigation fails. By offering a standardized, multi-sensory resource, he has accelerated progress in reliable autonomous driving and robotics. His research is widely recognized for its practical impact, bridging the gap between theoretical models and real-world deployment, and continues to inspire new approaches in sensor integration and navigation under adverse conditions.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
The NavINST Dataset for Multi-Sensor Autonomous Navigation
7 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Queen's University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago