Junshan Leng

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About

Junshan Leng is a robotics researcher whose work pushes the boundaries of perception beyond traditional visual sensing. His primary research areas include robotic manipulation, radio-frequency (RF) sensing, and sensor fusion for autonomous systems in cluttered or occluded environments. Leng’s most notable contribution is the development of RF-Grasp, a novel robotic system that uses radio-frequency signals to locate and grasp objects that are completely hidden from sight—such as those inside boxes or behind walls. This breakthrough overcomes the fundamental line-of-sight limitations of cameras and LiDAR, enabling robots to operate in unknown, unstructured spaces where vision fails. His paper on this work, published in 2021, has already garnered 7 citations, reflecting its early impact on the field of robotic perception. By integrating RF sensing with deep learning and motion planning, Leng has opened new avenues for search-and-rescue, warehouse automation, and assistive robotics. His research stands at the exciting intersection of hardware innovation and intelligent control, promising to make robots far more capable in real-world, visually obstructed environments.