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About

Shize Jiang is a pioneering researcher in neural engineering and brain-machine interfaces (BMI), with a focus on restoring motor function for individuals with severe paralysis. His work centers on decoding hand movements from intracranial neural signals, particularly using stereo-electroencephalography (SEEG) depth electrodes—a less invasive technique that records activity from deep brain structures. In his seminal 2017 study, Jiang demonstrated that SEEG signals from the central sulcus could reliably encode hand-movement-related modulation, laying the groundwork for prosthetic hand control. His subsequent 2020 work, cited 19 times, advanced this by showing that signals from the posterior parietal cortex significantly enhance gesture decoding performance, achieving higher accuracy for complex hand movements. With a total of 46 citations across his most-cited papers, Jiang’s contributions highlight the potential of SEEG-based BMIs to provide intuitive, high-fidelity control of robotic prosthetics. His research bridges fundamental neuroscience and clinical application, offering a promising pathway toward restoring functional independence for paralyzed patients through precise neural decoding.