Shubodh Sai is an independent researcher specializing in robot learning with eight years of experience spanning academic research and applied autonomy. He completed an MS by Research at IIIT Hyderabad, contributing to cross-modal localization and foundation-model adaptations (SAM, DINO) with publications at ECCV, ICRA, and WACV, and has since moved into independent research and applied robot learning. His background blends mechanical engineering (BITS Pilani) with deep learning for perception and navigation, including work on LiDAR-image pretraining and unsupervised aggregation for visual place recognition. He has experience leading teaching and engineering efforts—serving as head TA for Mobile Robotics and co-founding Sally Robotics to build AI-assisted navigation for Indian roads. Beyond publications, he experiments publicly through a research blog and maintains an active presence documenting research outputs and ideas. Practical, research-driven, and product-aware, he focuses on bridging foundational models with deployable robotic systems.
8 years of coding experience
5 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and Science
MS by Research, Computer Science, MS by Research, Computer Science at IIIT Hyderabad
Contributions:91 pushes, 4 branches in 1 year 5 months
localizationvisual-localization
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Shubodh Sai - Independent Researcher at fexponential