Tara Boroushaki

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About

Tara Boroushaki is pioneering the fusion of radio frequency (RF) perception with robotic manipulation, enabling machines to see and interact with objects hidden from sight. Her core research lies at the intersection of robotics, RF sensing, and multi-modal perception, tackling the fundamental challenge of grasping and retrieving fully-occluded items. Her landmark work, "RFusion" (2021, 40 citations), introduced a robotic arm that uses an RFID antenna and camera to locate and retrieve tagged objects even when completely hidden, effectively giving robots a form of "x-ray vision." She extended this with "RF-Grasp" (2021), which demonstrated the first system capable of grasping untagged, fully-occluded objects in unstructured environments by leveraging RF reflections. More recently, her "FuseBot" series (2022-2023) advanced mechanical search by combining RF and visual data to efficiently retrieve both rigid and deformable objects, while her "RL2" system (2024) applies reinforcement learning to optimize the speed and accuracy of RFID tag localization. With over 60 citations across her key publications, Boroushaki’s work is fundamentally reshaping how robots perceive and interact with cluttered, non-line-of-sight environments, promising transformative applications in warehouse logistics, manufacturing, and assistive robotics.