Nazish Naeem

Papers

Total Citations

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About

Nazish Naeem is a robotics researcher whose work lies at the intersection of perception, manipulation, and multi-modal sensing. Her key research area focuses on solving the challenging problem of **mechanical search**—enabling robots to retrieve occluded or hidden objects in cluttered environments. Naeem’s major contribution is the development of **FuseBot**, a system that fuses radio-frequency (RF) signals with visual data to locate and extract both rigid and deformable objects. Unlike traditional vision-only approaches, FuseBot leverages RF tags to pinpoint targets even when they are completely hidden from the camera, dramatically reducing search time and improving retrieval success. Her two most-cited papers on FuseBot, published in 2022 and 2023, have each garnered **6 citations**—a strong start for early-career work in a rapidly evolving field. This multi-modal strategy represents a significant step forward in robotic manipulation, offering a practical solution for real-world scenarios where objects are buried or obscured. Naeem’s research is particularly notable for its focus on **deformable objects**, a notoriously difficult category for robotic grasping. Her work has implications for warehouse automation, assistive robotics, and search-and-rescue operations, establishing her as a promising voice in modern robotics.