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About

Manikandasriram Srinivasan Ramanagopal is a robotics and computer vision researcher whose work spans autonomous perception, neural scene representations, and multi-modal sensor fusion. His research addresses fundamental challenges in enabling robots to reliably understand and navigate complex environments, from terrestrial autonomous vehicles to underwater marine systems. Among his most influential contributions is **LiStereo** (38 citations), which pioneered a fusion approach combining LiDAR and stereo imagery to generate dense, high-resolution depth maps — overcoming the cost and sparsity limitations of LiDAR alone. His work on **WaterNeRF** (39 citations) extended neural radiance fields to underwater environments, tackling the notoriously difficult problem of water column effects like attenuation and backscattering that degrade marine robot perception. His **CLONeR** framework (23 citations) further advanced NeRF-based scene understanding by integrating camera and LiDAR data with occupancy grids for robust outdoor neural representations. Beyond neural representations, Ramanagopal has contributed to autonomous 3D structure mapping, motion planning, and thermal video deblurring for low-light robotics. Collectively, his research reflects a consistent focus on making robotic perception more accurate, affordable, and deployable across challenging real-world conditions — a body of work that has garnered over 110 citations across diverse robotics and vision communities.