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About

Katie Zhuang is a leading researcher at the intersection of neural engineering and robotics, specializing in brain-machine interfaces (BMIs) and assistive technologies. Her work focuses on decoding neural signals to restore movement and sensation, with major contributions to both upper and lower limb prosthetics. Her most influential paper, "Active tactile exploration using a brain–machine–brain interface" (2011, 634 citations), pioneered the integration of sensory feedback into BMI systems, enabling users to actively explore objects through a closed-loop neural control paradigm. This foundational work demonstrated how bidirectional communication between brain and machine could enhance dexterity and embodiment. Zhuang further advanced the field with "Shared human–robot proportional control of a dexterous myoelectric prosthesis" (2019, 146 citations), introducing a collaborative control framework that blends user intent with robotic autonomy for more intuitive prosthetic use. In a notable achievement, she co-developed EXiO, a brain-controlled lower limb exoskeleton for rhesus macaques (2017, 38 citations), providing a proof-of-concept for translating intracortical BMI technology to gait rehabilitation. Her research has profound implications for restoring mobility and independence in individuals with paralysis or limb loss, bridging fundamental neuroscience with real-world clinical applications.