Jinling Lian

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About

Dr. Jinling Lian is a pioneering researcher at the intersection of neural engineering and intelligent transportation systems. Her work focuses on decoding human brain signals to create direct brain-to-vehicle interfaces, with transformative implications for assistive mobility and human-automation interaction. Her most-cited paper, "Queuing Network Modeling of Driver EEG Signals-Based Steering Control" (2016, 46 citations), introduces a groundbreaking framework that models how drivers can steer vehicles using electroencephalography (EEG) signals instead of physical limb movements. This work not only offers a pathway to independence for individuals with severe motor disabilities but also proposes a complementary control modality for the broader driving population. By integrating queuing network theory with neural signal processing, Lian provides a predictive model of driver performance in brain-controlled steering, advancing the feasibility of non-invasive brain-computer interfaces in real-world vehicular applications. Her research bridges cognitive science, control engineering, and human factors, laying the foundation for safer, more inclusive autonomous systems. With her innovative approach, Lian is shaping the future of human-vehicle symbiosis.