Yanming Xu
Papers
1
Total Citations
7
H-Index
1
About
Yanming Xu is a leading researcher in underwater acoustics and computational simulation, whose work bridges the gap between sonar imaging and advanced numerical modeling. Their most notable contribution is the development of a novel NeuS-assisted boundary element approach for underwater acoustic simulation from multi-view sonar images, published in 2025 and already garnering 7 citations. This innovative method integrates neural implicit surface representations with boundary element techniques, enabling highly accurate and efficient reconstruction of acoustic fields from sparse sonar data—a critical advancement for autonomous underwater vehicle navigation, marine archaeology, and environmental monitoring. Xu’s research addresses fundamental challenges in inverse acoustic problems, particularly in handling complex geometries and limited observational data. By combining machine learning with classical physics-based simulation, they have opened new pathways for real-time acoustic modeling in cluttered underwater environments. Their work is recognized for its practical impact, offering a scalable solution that reduces computational costs while maintaining fidelity. As a rising voice in computational acoustics, Yanming Xu is shaping the future of underwater sensing and simulation, with their methods poised to influence both academic research and industrial applications in ocean engineering.
Research Focus
Key Achievements
Top Papers
- 1