Raymond Phan
Papers
1
Total Citations
2
H-Index
1
About
Raymond Phan is a leading researcher in robotics perception and 3D computer vision, with a particular focus on advancing Light Detection and Ranging (LiDAR) technology for autonomous systems. His work addresses the critical challenge of extracting reliable geometric information from sparse sensor data—a fundamental problem in real-world robotics. Phan’s most cited paper, “Fast and Robust Normal Estimation for Sparse LiDAR Scans” (2024, 2 citations), introduces a novel method for computing surface normals from the inherently sparse output of mechanical LiDAR sensors. This contribution is vital for tasks such as object detection, mapping, and localization in autonomous vehicles and mobile robots. By developing algorithms that are both computationally efficient and resilient to noise, Phan has helped bridge the gap between theoretical computer vision and practical deployment in resource-constrained systems. His research directly impacts the reliability of robots operating in unstructured environments, making him a key figure in the ongoing effort to create safer, more perceptive autonomous technologies.
Research Focus
Key Achievements
Top Papers
- 1Fast and Robust Normal Estimation for Sparse LiDAR Scans2 citations · 2024