Jennifer Leahy

University of New Brunswick

Papers

1

Total Citations

5

H-Index

1

About

Dr. Jennifer Leahy is a leading researcher in autonomous systems and sensor fusion, specializing in the critical challenge of aligning multimodal data for enhanced spatial perception. Her work centers on registering 2D optical camera images with 3D light detection and ranging (LiDAR) point clouds, a fundamental task for autonomous driving, robotics, and geographic information systems. Her most-cited paper, "Enhancing Cross-Modal Camera Image and LiDAR Data Registration Using Feature-Based Matching" (2025), tackles the core difficulty of aligning data from sensors with distinct coordinate systems and orientations. By developing robust feature-based matching techniques, Leahy has advanced the accuracy and reliability of cross-modal registration, directly improving environmental awareness in self-driving vehicles and robotic navigation. With 5 citations already for this recent work, her contributions are quickly gaining recognition. Dr. Leahy’s research bridges a key gap in sensor integration, enabling more precise scene understanding and safer autonomous operation—a vital step toward fully reliable intelligent systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
5
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Enhancing Cross-Modal Camera Image and LiDAR Data Registration Using Feature-Based Matching
5 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of New Brunswick

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago