Dr. Naishi Feng | Virtual Reality – Lecturer at Shenyang University, China
Naishi Feng is a highly accomplished academic with a focus on neuroengineering, mechatronic systems, and intelligent sensor technologies. As a Lecturer at the College of Intelligent Science and Information Engineering, Shenyang University, she has consistently contributed to advancements in understanding motor imagery, brain-machine interfaces, and neurorehabilitation technologies. Her journey from a robust educational background to postdoctoral work at prestigious institutions has enabled her to establish a reputation in the intersection of neuroengineering and intelligent systems. With a commitment to excellence and innovation, Naishi Feng is a recognized leader in her field.
Profile:
Education:
Naishi Feng’s academic path reflects a strong foundation in both engineering and neurotechnology. She completed her Ph.D. in Mechatronic Engineering at Northeastern University in 2023, where her research laid the groundwork for her future studies in neuroengineering. During her doctoral studies, she honed her skills in sensor systems and motor intention decoding. In addition to her Ph.D., Naishi earned her Master’s degree in Mechatronic Engineering at Northeastern University in 2018, and her Bachelor’s in Mechanical Design, Manufacturing, and Automation from Shenyang Jianzhu University in 2016. These qualifications are complemented by a visiting scholar position at the Department of Neurorehabilitation Sciences, KU Leuven, Belgium (2021–2022), where she expanded her expertise in neurorehabilitation technologies and motor intention decoding.
Experience:
Naishi Feng has gained invaluable research experience both in academic institutions and through postdoctoral positions. Since 2024, she has been a Postdoctoral Fellow at both Northeastern University and Shenyang University Science and Technology Park. Her previous postdoctoral work at The Chinese University of Hong Kong’s Brain and Mind Institute (2023–2024) was pivotal in advancing her research on neurorehabilitation and brain-computer interfaces. Naishi’s academic career is also enriched by her role as a Lecturer at Shenyang University, where she imparts her knowledge in intelligent systems, artificial intelligence, and neurotechnology, while also leading groundbreaking research in related fields.
Research Interests:
Naishi Feng’s research interests primarily revolve around neuroengineering, focusing on decoding motor intentions, brain-machine interfaces, and sensor technologies. Her expertise includes applying graph convolutional networks for upper-limb motor imagery decoding and investigating the neural basis of motion sickness using EEG signals. She is also passionate about soft sensor array designs for controlling prosthetic devices through sEMG (surface electromyography). Naishi’s work explores how these innovations can be used in neurorehabilitation, robotics, and even virtual reality to improve quality of life for individuals with neurological disorders. Her interdisciplinary research aims to bridge the gap between engineering, neuroscience, and rehabilitation technologies.
Awards:
While Naishi Feng has yet to receive specific major awards, her research has undoubtedly garnered significant recognition in her field. Her groundbreaking work has been cited by numerous articles in high-impact journals, showcasing the influence of her contributions to the field of neuroengineering and mechatronics. Naishi’s continued work in the fields of motor imagery, neurorehabilitation, and sensor systems positions her as a leading researcher in her domain, and her dedication to advancing technology continues to make a significant impact in academia and industry.
Publications:
Naishi Feng has contributed to several high-profile publications that underscore her expertise and pioneering work in neuroengineering and mechatronics. Here are some of her key publications:
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Feng, N., Hu, F., Wang, H., & Gouda, M. A. (2020). Decoding of Voluntary and Involuntary Upper-Limb Motor Imagery Based on Graph Fourier Transform and Cross-Frequency Coupling Coefficients, Journal of Neural Engineering, 17(5): 1741-2552 🧠 (Cited by: 100+)
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Feng, N., Xin, Y., Gong, J., Wang, H., & Hu, F. (2021). Self-Adaption Soft Sensor Array Design for sEMG Control, IEEE Sensors Journal, 21(6): 8367-8374 🤖 (Cited by: 70+)
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Feng, N., Hu, F., Wang, H., & Zhao, Z. (2021). Hybrid Graph Convolutional Networks for Skeleton-Based and EEG-Based Jumping Action Recognition, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 🏅 (Cited by: 50+)
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Feng, N., Hu, F., Wang, H., & Zhou, B. (2021). Motor Intention Decoding from the Upper Limb by Graph Convolutional Network Based on Functional Connectivity, International Journal of Neural Systems, 31(12): 2150047 💡 (Cited by: 60+)
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Feng, N., Zhou, B., Zhang, Q., Hua, C., & Yuan, Y. (2025). A Comprehensive Exploration of Motion Sickness Process Analysis from EEG Signal and Virtual Reality, Computer Methods and Programs in Biomedicine, 264(2025): 108714 🌐 (Cited by: N/A)
Conclusion:
Naishi Feng is an exceptional researcher with a deep commitment to advancing the fields of neuroengineering and intelligent systems. Her educational background, extensive experience, and research in neurorehabilitation technologies position her as a leader in her field. With numerous high-impact publications and ongoing contributions to cutting-edge technologies, Naishi has made significant strides in understanding motor imagery, brain-machine interfaces, and motion sickness analysis. Her innovative work has the potential to significantly improve the quality of life for individuals with neurological disorders and further advance the integration of neurotechnology and robotics. Naishi Feng is a highly deserving candidate for the “Best Researcher Award” and will undoubtedly continue to push the boundaries of research and technological advancement in her field.