Jaehyeok Doh

Gyeongsang National University

Papers

1

Total Citations

87

H-Index

1

About

Jaehyeok Doh is a leading researcher at the intersection of autonomous driving, smart mobility, and 3D data processing. His work focuses on overcoming critical challenges in perception systems for autonomous vehicles, particularly in the compression, processing, and learning of LiDAR point cloud data—a key sensor technology for safe navigation. His highly cited 2022 paper, “LiDAR Point Cloud Compression, Processing and Learning for Autonomous Driving,” with 87 citations, provides a comprehensive survey that has become a foundational reference for researchers tackling the trade-offs between data fidelity and real-time performance. By addressing the vulnerabilities inherent in unmanned vehicle perception, Doh’s contributions directly impact the safety and reliability of smart city infrastructure. His research not only advances algorithmic efficiency but also underscores the ethical imperative of robust sensing in life-critical applications. Through his work, Doh is shaping the next generation of autonomous systems, making him a pivotal figure in the drive toward safer, smarter urban mobility.

Research Focus

Key Achievements

1
H-Index
1
Papers
87
Total Citations
87
Avg Citations/Paper
🏆 Most Cited Paper
Lidar Point Cloud Compression, Processing and Learning for Autonomous Driving
87 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Gyeongsang National University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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