Nhu-Nghia Bui

Papers

2

Total Citations

10

H-Index

2

About

Dr. Nhu-Nghia Bui is a leading researcher in efficient deep learning for autonomous mobile robotics, specializing in semantic segmentation, monocular depth estimation, and reinforcement learning-based path planning. His work addresses the critical challenge of deploying high-performance neural networks on resource-constrained mobile robots. Dr. Bui’s major contributions include the development of KD-SegNet, a knowledge distillation framework that dramatically reduces model size while preserving segmentation accuracy, achieving 6 citations since 2025. He also introduced ELDE-Net, a lightweight depth estimation network designed to enhance 3D object detection and enable robust, real-time path planning for deep reinforcement learning agents, garnering 4 citations. These innovations directly tackle the fundamental trade-off between model performance and computational efficiency, making advanced perception and navigation feasible for practical mobile robot applications. Dr. Bui’s work is notable for its focus on deployable, real-world solutions, bridging the gap between state-of-the-art deep learning and the stringent hardware limitations of autonomous systems. His research continues to influence the development of smarter, more efficient mobile robots for navigation and scene understanding.

Research Focus

Key Achievements

2
H-Index
2
Papers
10
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
KD-SegNet: Efficient Semantic Segmentation Network with Knowledge Distillation Based on Monocular Camera
6 citations · 2025
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 3

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago