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About

Jinhua Zhang is a pioneering researcher at the intersection of soft robotics, brain-computer interfaces (BCI), and rehabilitation engineering, whose work has profoundly shaped how assistive and biomedical technologies are designed and controlled. With over 650 citations across his most influential publications, Zhang has established himself as a leading voice in human-machine interaction and intelligent robotic systems. His most celebrated contributions include a multimodal EEG/EMG/EOG-based interface for controlling a soft robot hand (140 citations) and an innovative electrostatic layer jamming technique for tunable stiffness in soft robots (138 citations), both published in 2019. These works elegantly bridge neuroscience and mechanical engineering to advance motor rehabilitation for stroke survivors. Zhang has also made significant strides in BCI signal classification, proposing multi-class Adaboost extreme learning machine approaches for distinguishing motor imagery states with greater accuracy. Beyond rehabilitation, Zhang's research spans biohybrid robots actuated by living cells, acoustically driven microrobots for minimally invasive applications, and biomimetic locomotion systems inspired by inchworms. His geometric soft-rigid hybrid actuators further demonstrate a knack for elegant mechanical innovation. Collectively, Zhang's body of work represents a uniquely interdisciplinary vision — uniting neuroscience, materials science, and robotics to improve human health and capability.