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About

Shaomin Zhang is a neuroscience and biomedical engineering researcher whose work sits at the dynamic intersection of neural interfaces, rehabilitation robotics, and brain-machine interfaces (BMIs). His research spans two complementary frontiers: decoding neural signals to restore lost motor function and developing assistive robotic systems for individuals with spinal cord injuries and stroke. Zhang's early contributions explored how dorsolateral periaqueductal gray stimulation could govern immobile behavior in animal-robot navigation systems, a novel approach that earned his most-cited work 17 citations. His investigations into probabilistic and recurrent neural network architectures for decoding neural velocity signals have advanced the precision of BMI technology, while his rat-robot behavior control studies demonstrate a sophisticated command of closed-loop neural systems. On the rehabilitation side, Zhang led the development of lower-limb medical exoskeletons at SIAT, Shenzhen, contributing real-time gait planning strategies and adaptive joint control methods to help paraplegic patients walk independently. His 2024 work on somatosensory integration in robot-assisted stroke rehabilitation reflects his evolving focus on reconstructing sensorimotor pathways. Collectively, Zhang's portfolio represents a sustained and impactful effort to bridge fundamental neuroscience with practical clinical engineering solutions.