Papers
2
Total Citations
15
H-Index
2
About
Pan Han is a researcher whose work bridges the frontiers of underwater robotics and bio-inspired fluid dynamics. His primary research areas include autonomous underwater vehicle (AUV) perception, multi-beam sonar imaging, and the hydrodynamics of fish schooling. Han’s most notable contribution is the development of UUVDNet, an efficient deep-learning-based target detection network for multibeam forward-looking sonar, published in 2024 and already garnering 10 citations—a strong indicator of its immediate impact in the field of underwater computer vision. This work addresses a critical challenge in real-time obstacle detection for unmanned underwater vehicles operating in cluttered environments. In parallel, Han has made significant strides in understanding collective swimming energetics. His 2020 study on the effect of formation patterns on schooling energetics in fish-like swimming, which employs an immersed-boundary-method numerical solver, has earned 5 citations and provides foundational insights into how spatial arrangement influences energy efficiency—insights that could inspire more efficient multi-AUV formations. By combining cutting-edge neural network architectures with classical fluid dynamics, Pan Han exemplifies a modern interdisciplinary engineer, advancing both the practical deployment of autonomous underwater systems and the fundamental science of aquatic locomotion.
Research Focus
Key Achievements
Top Papers
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