Jiafeng Cui

National University of Defense Technology

Papers

1

Total Citations

15

H-Index

1

About

Dr. Jiafeng Cui is a leading researcher in robotics and autonomous driving, with a primary focus on LiDAR-based perception and place recognition. His most influential work, "CCL: Continual Contrastive Learning for LiDAR Place Recognition" (2023, 15 citations), addresses a critical bottleneck in long-term autonomous navigation: the inability of deep learning models to adapt to changing environments without catastrophic forgetting. By introducing a continual contrastive learning framework, Dr. Cui enables LiDAR place recognition systems to incrementally learn new places while retaining knowledge of previously seen locations—a breakthrough for robust loop closure and global localization. This work has quickly gained traction in the robotics community for its practical impact on real-world deployment. Beyond this, Dr. Cui’s research spans sensor fusion, 3D scene understanding, and lifelong learning for autonomous systems. His contributions are shaping the next generation of resilient, adaptive perception systems, making him a rising voice in the field. For students and researchers, Dr. Cui’s work exemplifies how thoughtful algorithmic design can solve persistent challenges in robotics.

Research Focus

Key Achievements

1
H-Index
1
Papers
15
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
CCL: Continual Contrastive Learning for LiDAR Place Recognition
15 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: National University of Defense Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago