Zhanpeng Jin

University of Pittsburgh, University at Buffalo, State University of New York, South China University of Technology

Papers

Total Citations

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About

Zhanpeng Jin is a pioneering researcher at the intersection of brain-computer interfaces (BCI), neural prosthetics, and intelligent robotic systems. His work fundamentally explores how neural signals can be decoded to control external devices, with a particular focus on aiding mobility-impaired individuals. Jin’s early foundational research, such as his 2009 paper on using artificial neural networks to translate neuromuscular activation into locomotion, laid the groundwork for neural prostheses. This work has garnered 10 citations, establishing a base for his later innovations. More recently, Jin has pushed the boundaries of multi-user BCI systems. His 2024 study, "NeuroBCI," introduces a groundbreaking framework for multi-brain to multi-robot interaction, leveraging EEG-adaptive neural networks and semantic communications—a concept that could revolutionize collaborative human-robot teams in home and professional settings. Additionally, his 2022 work "DeepBrain" (9 citations) advances EEG-based BCI for assistive tasks. Beyond BCI, Jin has contributed to embedded systems, developing neural network accelerators for real-time tracking in UAVs and mobile robots (2018, 2 citations). Through his research, Jin is not only decoding the mind but also building the bridges that connect human intention to machine action, promising a future where thought alone can command robotic assistance.