Tejas Zodage

Carnegie Mellon University, Birla Institute of Technology and Science, Pilani

Papers

Total Citations

H-Index

About

Tejas Zodage is a robotics researcher whose work spans the critical intersection of perception, manipulation, and sustainable automation. His primary research areas include point-cloud registration, robotic locomotion, and intelligent waste sorting. Zodage’s most impactful contribution is his work on globally optimal registration of noisy point clouds, where he tackles the fundamental challenge of finding the best alignment between 3D scans without getting trapped in local minima—a problem that plagues standard methods like ICP. His paper “Correspondence Matrices are Underrated” (2020, 10 citations) challenges conventional wisdom in point-cloud registration, proposing that careful handling of correspondence matrices can unlock more robust solutions for applications in SLAM and robotic manipulation. Zodage also demonstrates impressive breadth: his “2DxoPod” project (2020, 7 citations) introduces a modular robot that mimics vertebrate locomotion, while his “RGB-X Classification for Electronics Sorting” (2022, 5 citations) applies computer vision to the pressing problem of e-waste recycling, aiming to make supply chains more sustainable. With over 25 total citations and a growing portfolio that bridges theory and real-world impact, Zodage is establishing himself as a versatile roboticist whose work could help robots both see more clearly and build a greener future.