KiDong Lee
Papers
1
Total Citations
28
H-Index
1
About
Dr. KiDong Lee is a leading researcher in autonomous systems and robotics, with a primary focus on sensor fusion and real-time object perception. His most-cited work, "An Advanced Approach to Object Detection and Tracking in Robotics and Autonomous Vehicles Using YOLOv8 and LiDAR Data Fusion" (2024), tackles a critical bottleneck in autonomous driving: the unreliability of vision-only systems under poor lighting, occlusion, and complex environments. By fusing YOLOv8’s deep learning capabilities with LiDAR point cloud data, Dr. Lee demonstrated a robust framework that significantly improves detection accuracy and tracking stability—a breakthrough with 28 citations in under a year, signaling strong early impact. His contributions lie at the intersection of computer vision, deep learning, and robotics, offering practical solutions for safer autonomous navigation. Dr. Lee’s work is particularly notable for its applied focus, bridging cutting-edge AI with real-world hardware constraints. For students and researchers entering the field, his research exemplifies how sensor fusion can overcome the fundamental limitations of single-modality perception, making him a key figure to follow in the evolution of autonomous vehicle technology.
Research Focus
Key Achievements
Top Papers
- 1