Shiwei Li
Papers
1
Total Citations
7
H-Index
1
About
Shiwei Li is a rising researcher in the field of underwater acoustics and computational imaging, with a focus on bridging the gap between sonar data and realistic acoustic simulation. His work centers on developing novel methods for reconstructing underwater environments from multi-view sonar imagery, a critical challenge for autonomous underwater vehicles and marine robotics. In his most-cited paper, "Underwater acoustic simulation from multi-view sonar images: A NeuS-assisted boundary element approach" (2025), Li introduces a pioneering framework that integrates neural implicit surface representations with boundary element methods to generate high-fidelity acoustic simulations. This approach enables accurate modeling of sound propagation and scattering in complex underwater scenes, significantly improving the realism and utility of synthetic sonar data for training perception systems. Although early in his career, with this work already garnering 7 citations, Li’s contribution stands out for its innovative fusion of machine learning and classical acoustics, offering a scalable solution to the data scarcity problem in underwater sensing. His research holds promise for advancing autonomous navigation, marine archaeology, and environmental monitoring, marking him as a notable emerging voice in acoustic simulation and sonar-based perception.
Research Focus
Key Achievements
Top Papers
- 1