Advaith V. Sethuraman
Papers
7
Total Citations
90
H-Index
4
About
Advaith V. Sethuraman is an emerging researcher whose work sits at the intersection of underwater robotics, marine perception, and machine learning. His research focuses on developing advanced computational methods to address the unique challenges of underwater imaging and robot navigation, where degraded visual conditions and complex acoustic environments demand specialized solutions. Sethuraman's most recognized contribution, "WaterNeRF: Neural Radiance Fields for Underwater Scenes," has garnered 39 citations and represents a pioneering application of neural radiance field technology to underwater environments, tackling the distorting effects of water attenuation and backscattering. His benchmark dataset for shipwreck segmentation from side-scan sonar imagery (28 citations) has provided the broader research community with a critical open-source resource for advancing marine machine learning. Additional work includes TURTLMap, a real-time dense mapping solution for low-texture underwater settings, and OceanSim, a GPU-accelerated simulation framework for underwater robot perception. His most recent contributions — SonarSplat, which applies Gaussian splatting to imaging sonar — demonstrate a continued commitment to pushing the frontier of underwater scene reconstruction. Across his portfolio, Sethuraman is establishing himself as a key contributor to enabling more capable, autonomous marine robotic systems.
Research Focus
Key Achievements
Top Papers
- 1WaterNeRF: Neural Radiance Fields for Underwater Scenes39 citations · 2023
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- 6SonarSplat: Novel View Synthesis of Imaging Sonar via Gaussian Splatting2 citations · 2025
- 7WaterNeRF: Neural Radiance Fields for Underwater Scenes2 citations · 2022