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About

Chandra Kambhamettu is a leading researcher at the intersection of computer vision, medical imaging, and human-centered AI. His work is defined by a unique ability to solve real-world localization and navigation problems—whether for a visually impaired person in a building or a surgeon performing robotic prostatectomy. A central theme is **image-based indoor localization**, where he pioneered methods using multi-view images and 3D Structure-from-Motion (SfM) models to determine location without relying on WiFi or cellular signals. His influential paper “Where am I in the dark” (77 citations) advanced this field by applying active transfer learning to thermal imaging, enabling robust localization even in low-light conditions. In medical applications, Kambhamettu has made significant contributions to **mixed and virtual reality surgical guidance**, developing a VR tool for robotic-assisted radical prostatectomy that integrates multiparametric MRI data, and a mixed reality system for real-time navigation during laparoscopic surgery. His work on the “Benchmark Grocery Dataset of Realworld Point Clouds” (2024) extends his expertise to fine-grained 3D object recognition for assistive technologies. With over 200 publications and a consistent focus on translating vision algorithms into practical tools, Kambhamettu’s research has a tangible impact on both clinical practice and everyday navigation.