Ganesh Nagaraja

Papers

Total Citations

278

H-Index

About

Ganesh Nagaraja is a researcher specializing in computer vision and robotic manipulation, with a particular focus on solving challenging perception problems that bridge the gap between artificial systems and real-world environments. His most notable contribution is **ClearGrasp**, a groundbreaking framework for estimating the 3D shape of transparent objects — a notoriously difficult problem in robotics and computer vision. Transparent objects such as glasses, bottles, and containers present unique challenges for standard depth sensors, which typically produce noisy or unreliable readings due to the objects' light-refracting properties. ClearGrasp addresses this by enabling accurate depth reconstruction of such objects, making robotic grasping and manipulation significantly more reliable in practical settings. Published across iterations in 2019 and 2020, ClearGrasp has garnered over 258 citations, reflecting its substantial influence on the robotics and vision communities. The work has become a key reference point for researchers tackling transparent and reflective object perception — an area increasingly relevant as robots are deployed in household and industrial environments filled with such objects. Nagaraja's contributions represent an important step toward more robust, generalizable robotic perception systems capable of operating in unstructured, real-world conditions.