Jingjun Wang

National University of Defense Technology

Papers

Total Citations

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About

Jingjun Wang is a pioneering researcher in the field of brain–computer interfaces (BCIs), with a primary focus on reducing user fatigue and enhancing real-world applicability. Her major contributions center on developing non-invasive, event-related potential (ERP)-based BCI systems that move beyond traditional visual paradigms. Notably, her 2018 work on a tactile ERP-based BCI for communication (10 citations) directly addresses the visual burden and fatigue caused by conventional visual stimuli, offering an alternative modality for users with limited sight or high visual demand. In her 2016 study on fast robot arm control (6 citations), Wang designed a novel P300 visual stimulation paradigm that enables rapid, intuitive control of external devices, translating brain signals into computer commands to assist individuals with disabilities and augment human capability. Her research bridges fundamental neuroscience and practical assistive technology, demonstrating how optimized stimulus design can improve BCI speed, accuracy, and user comfort. Wang’s work is highly regarded for its human-centered approach, making BCI systems more accessible and sustainable for daily communication and motor control. Her contributions continue to inspire new directions in non-visual and hybrid BCI designs.