Huynh Vu Nhu Nguyen

FPT University

Papers

1

Total Citations

21

H-Index

1

About

Huynh Vu Nhu Nguyen is a rising researcher in autonomous driving systems, with a focus on integrating computer vision and robotics control. His most-cited work, "Optimizing YOLO Performance for Traffic Light Detection and End-to-End Steering Control for Autonomous Vehicles in Gazebo-ROS2" (2023, 21 citations), addresses a critical bottleneck in self-driving technology: the need for robust, real-time perception and control. Nguyen’s key contributions lie in optimizing the YOLO object detection framework specifically for traffic light recognition, and then coupling this with an end-to-end steering control pipeline within the Gazebo-ROS2 simulation environment. This work moves beyond traditional color- and shape-based detection methods, which are often brittle in varying lighting and weather conditions, toward a more adaptive, learning-based approach. By demonstrating a fully integrated system—from perception to actuation—Nguyen provides a practical blueprint for deploying deep learning in autonomous vehicle control. His research is particularly notable for its emphasis on simulation-to-reality transfer, a crucial step for safe and scalable autonomous driving development. With a growing citation record and a focus on applied AI for robotics, Nguyen is establishing himself as a promising voice in the next generation of autonomous vehicle engineers.

Research Focus

Key Achievements

1
H-Index
1
Papers
21
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Optimizing YOLO Performance for Traffic Light Detection and End-to-End Steering Control for Autonomous Vehicles in Gazebo-ROS2
21 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: FPT University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago