Sen Gao
Papers
1
Total Citations
5
H-Index
1
About
Sen Gao is a leading researcher in underwater robotics and autonomous perception, with a focus on real-time sonar image processing for autonomous underwater vehicles (AUVs). His most notable contribution is the development of a lightweight YOLO network that leverages temporal features for high-resolution sonar segmentation, a breakthrough that addresses the critical computational bottleneck in dynamic underwater environments. This work, published in 2025 and already garnering 5 citations, demonstrates Gao’s ability to bridge deep learning efficiency with practical AUV deployment, enabling faster and more accurate environmental sensing. His research directly impacts the fields of marine exploration, underwater navigation, and autonomous systems, where real-time perception is essential. Gao’s innovative approach to combining temporal dynamics with lightweight architectures marks him as a rising figure in robotics and computer vision, with his work poised to influence future generations of underwater autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1