Jin Jing, Professor and Doctoral Supervisor. He is member of international BCI Award Foundation (Europe) and member of Evaluation Committee for Young Scientist Award of International Brain Computer Interface Society. He serves as the Secretary General of the brain computer interface group of the Chinese society of Biomedical Engineering, the member of the Education Working Committee of the Chinese society of automation, and a distinguished expert of the Chinese society of automation. He also serves as the Associate Editor of Journal of Neuroscience Methods, Cognitive Neurodynamics and Frontiers in Neurorobotics, Action Editor of Neural Networks, Editor of Journal of Neural Engineering. At ECUST, he is the Chair of Automation Department and the head of the Lab for Brain-Computer Interfaces and Control.  

Prof. Jin has devoted decades to solve the key technology problems of brain computer interface system, and realized the clinical application of brain computer interface. Specifically, his notable achievements include: (i) Presented a new non-row/column flash pattern based on binomial coefficients code to overcome the problems of stimulus optimization for P300 Based BCI system. (ii) Presented online training methods to avoid the offline training of P300 BCI. (iii) Developed new brain computer interface systems for the assessment of state of consciousness, and active stroke rehabilitation.

Moreover, Prof. Jin published more than 130 papers in the Journal of neural engineering, a top journal in the field of brain computer interface, IEEE Transactions on neural networks and learning systems, a top journal of Chinese Academy of Sciences, 12 papers highly cited by ESI, and cited by academic Google for more than 5500 times. From 2015 to 2020, he was selected as the Most Cited Chinese Researchers in the field of Biomedical Engineering. He has won the second prize in Shanghai's Natural Science Award in 2018 (Ranking first). The team led by Prof. Jin won the title of “shanghai worker pioneer”. Relevant transformation results have obtained China's medical device registration certificate and production license.

Department: Department of Automation, School of Information Science and Engineering

Address: 130 Meilong Road, Shanghai

Work Phone: 021-64253808

E-mail: jinjing@ecust.edu.cn

Research Interests:

Technologies of Human-Computer Hybrid Intelligence, Human-Computer Interaction System, Rehabilitation Technologies for Stroke Patients, Intelligent Rehabilitation Robot

Professional Services:

Associate Editor of Journal of Neuroscience Methods

Associate Editor of Cognitive Neurodynamics

Associate Editor of Frontiers in Neurorobotics

Action Editor of Neural Networks

Editor of Journal of Neural Engineering

Editor of Computational Intelligence and Neuroscience

Editor of Brain Computer Interfaces

Editor of Science Progress

Editor of Applied Sciences

Editor of Electronics

Editor of Machines

Member of International BCI Award Foundation (Europe)

Member of Evaluation Committee for Young Scientist Award of International Brain Computer Interface Society

Teaching:

Brain Computer Interface and its Application

Principle and Technology of Brain Computer Interaction

Research Program:

• Jan. 2022 to Dec. 2026, Scientific and technological innovation 2030 - brain science and brain like research, 2022ZD0208900 (Project 4), Bi directional closed loop brain computer interface for rehabilitation of motor and consciousness disorders, PI

• July. 2021 to June. 2024, Shanghai Municipal Science and technology major projects, 2021SHZDZX (Project 5), Key technologies and core devices of brain computer interface, PI

• Jan.  2022 to Dec. 2025, National Natural Science Foundation of China, 62176090, Design and application of multi-class motor imagery paradigm based on motion perception, PI.

• Jan. 2016 to Dec. 2019, National Natural Science Foundation of China, 61573142, Optimization of stimulus-based brain computer interface paradigm and its application on patients, PI.

Publications:

• Jing Jin*, Hao Sun, Ian Daly, Shurui Li, Chang Liu, Xingyu Wang, and Andrzej Cichocki, A Novel Classification Framework Using the Graph Representations of Electroencephalogram for Motor Imagery based Brain-Computer Interface, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021, DOI: 10.1109/TNSRE.2021.3139095 

• Jing Jin*, Zhiqiang Wang, Ren Xu, Chang Liu, Xingyu Wang, and Andrzej Cichocki, Robust Similarity Measurement Based on a Novel Time Filter for SSVEPs Detection, IEEE Transactions on Neural Networks and Learning Systems, 2021, DOI: 10.1109/TNNLS.2021.3118468 

• Jing Jin*, Ruocheng Xiao, Ian Daly, Yangyang Miao, Xingyu Wang, and Andrzej Cichocki, Internal Feature Selection Method of CSP Based on L1-Norm and Dempster-Shafer Theory, IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(11): 4814-4825.

• Jing Jin*, Hua Fang, Ian. Daly, Ruocheng Xiao, Yangyang Miao, Xingyu Wang, and Andrzej Cichocki, Optimization of Model Training Based on Iterative Minimum Covariance Determinant in Motor-Imagery BCI, International Journal of Neural Systems, 2021, 31(7): 2150030.

• Jing Jin*, Chang Liu, Ian Daly, Yangyang Miao, Shurui Li, Xingyu Wang, and Andrzej Cichocki，Bispectrum-based Channel Selection for Motor Imagery based Brain-Computer Interfacing, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020, 28(10): 2153-2163.

• Jing Jin*, Zongmei Chen, Ren Xu, Yangyang Miao, Xingyu Wang, and Tzyy-Ping Jung, Developing a Novel Tactile P300 Brain-Computer Interface with a Cheeks-Stim Paradigm, IEEE Transactions on Biomedical Engineering, 2020, 67(9): 2585-2593.

• Jing Jin*, Shurui Li, Ian Daly, Yangyang Miao, Chang Liu, Xingyu Wang, and Andrzej Cichocki，The Study of Generic Model Set for Reducing Calibration Time in P300-based Brain-Computer Interface, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020, 28(1): 3-12.

• Jing Jin*, Yangyang Miao, Ian Daly, Cili Zuo, Dewen Hu, and Andrzej Cichocki, Correlation-based Channel Selection and Regularized Feature Optimization for MI-based BCI, Neural Networks, 2019, 118: 262-270.  

• Shurui Li, Jing Jin*, Ian Daly, Chang Liu, and Andrzej Cichocki, Feature selection method based on Menger curvature and LDA theory for a P300 brain-computer interface, Journal of Neural Engineering, 2021, DOI: 10.1088/1741-2552/ac42b4 

• Ruocheng Xiao, Yitao Huang, Ren Xu, Bei Wang, Xingyu Wang, and Jing Jin*. Coefficient-of-variation-based Channel Selection with a New Testing Framework for MI-based BCI, Cognitive Neurodynamics, 2021.DOI: 10.1007/s11571-021-09752-4 

• Zhiqiang Wang, Jing Jin*, Ren Xu, Chang Liu, Xingyu Wang, and Andrzej Cichocki, Efficient Spatial Filters Enhance SSVEP Target Recognition Based on Task-Related Component Analysis, IEEE Transactions on Cognitive and Developmental Systems, 2021, DOI: 10.1109/TCDS.2021.3096812

• Yitao Huang, Jing Jin*, Ren Xu, Yangyang Miao, Chang Liu, and AndrzejCichocki, Multi-view Optimization of Time-frequency Common Spatial Patterns for Brain-computer Interfaces, Journal of Neuroscience Methods, 2022, 365: 109378.

• Shurui Li, Jing Jin*, Ian Daly, Xingyu Wang, Hak-Keung Lam, and Andrzej Cichocki, Enhancing P300 Based Character Recognition Performance Using a Combination of Ensemble Classifiers and a Fuzzy Fusion Method, Journal of Neuroscience Methods, 2021, 362: 109300.

• Xinru Zhang, Jing Jin*, Shurui Li, Xingyu Wang, and Andrzej Cichocki, Evaluation of Color Modulation in Visual P300-speller Using New Stimulus Patterns, Cognitive Neurodynamics, 2021,15: 873–886. 

• Hao Sun, Jing Jin*, Ren Xu, and Andrzej Cichocki, Feature Selection Combining Filter and Wrapper Methods for Motor-Imagery Based Brain-Computer Interfaces, International Journal of Neural Systems, 2021, 31(9): 2150040. 

• Chang Liu, Jing Jin*, Ren Xu, Shurui Li, Cili Zuo, Hao Sun, Xingyu Wang, Andrzej Cichocki, Distinguishable Spatial-spectral Feature Learning Neural Network Framework for Motor Imagery-based Brain-computer Interface, Journal of Neural Engineering, 2021, 18(4): 0460e4. 

• Cili Zuo, Jing Jin*, Ren Xu, Lianghong Wu, Chang Liu, Yangyang Miao, and Xingyu Wang, Cluster Decomposing and Multi-objective Optimization-based Ensemble Learning Framework for Motor Imagery-based Brain-Computer Interfaces, Journal of Neural Engineering, 2021, 18(2): 026018. 

• Ying Mao, Jing Jin*, Ren Xu, Shurui Li, Yangyang Miao, and Andrzej Cichocki, The Influence of Visual Attention on the Performance of a Novel Tactile P300 Brain-Computer Interface with Cheeks-Stim Paradigm, International Journal of Neural Systems, 2021, 2021: 2150004. 

• Hao Sun, Jing Jin*, Wanzeng Kong*, Cili Zuo, Shurui Li, and Xingyu Wang, Novel Channel Selection Method Based on Position Priori Weighted Permutation Entropy and Binary Gravity Search Algorithm, Cognitive Neurodynamics, 2021, 15: 141–156.

• Yangyang Miao, Jing Jin*, Ian Daly, Cili Zuo, Xingyu Wang, Andrzej Cichocki, and Tzyy-Ping Jung. Learning Common Time-Frequency-Spatial Patterns for Motor Imagery Classification, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021, 29: 699-707. 

• Ying Mao, Jing Jin*, Shurui Li, Yangyang Miao, and Andrzej Cichocki, Effects of Skin Friction on Tactile P300 Brain-Computer Interface Performance, Computational Intelligence and Neuroscience, 2021, 2021: 6694310.

• Cili Zuo, Yangyang Miao, Xingyu Wang, Lianghong Wu*, and Jing Jin*, Temporal Frequency Joint Sparse Optimization and Fuzzy Fusion for Motor Imagery-based Brain-Computer Interfaces, Journal of Neuroscience Methods, 2020, 340: 108725.

• Cili Zuo, Jing Jin*, Erwei Yin, Rami Saab, Yangyang Miao, Xingyu Wang, Dewen Hu, and Andrzej Cichocki. Novel Hybrid Brain-Computer Interface System Based on Motor Imagery and P300, Cognitive Neurodynamics, 2020, 14(2): 253-265.

• Qianqian Liu, Yong Jiao, Yangyang Miao, Cili Zuo, Xingyu Wang, Andrzej Cichocki, and Jing Jin*，Efficient Representations of EEG Signals for SSVEP Frequency Recognition Based on Deep Multiset CCA, Neurocomputing, 2020, 378: 36-44.

• Yangyang Miao, Erwei Yin, Brendan Z. Allison, Yu Zhang Yan Chen, Yi Dong, Xingyu Wang, Dewen Hu, Andrzej Chchocki, and Jing Jin*, An ERP-based BCI with Peripheral Stimuli: Validation with ALS Patients, Cognitive Neurodynamics, 2020, 14(1): 21–33.

• Shurui Li, Jing Jin*, Ian Daly, Cili Zuo, Xingyu Wang, and Andrzej Cichocki, Comparison of The ERP-based BCI Performance among Chromatic (RGB) Semitransparent Face Patterns, Frontiers in Neuroscience, 2020, 14: 54.

• Yangyang Miao, Shugeng Chen, Xingru Zhang, Jing Jin*, Ren Xu, Ian Daly, Jie Jia*, Xingyu Wang, Andrzej Cichocki, and Tzyy-Ping Jung, BCI-based Rehabilitation on the Stroke in Sequela Stage. Neural Plasticity, 2020, 2020: 8882764.

• Zongmei Chen, Jing Jin*, Daly Ian, Cili Zuo, Xingyu Wang, and Andrzej Cichocki, Effects of Visual Attention on Tactile P300 BCI, Computational Intelligence and Neuroscience, 2020, 2020: 6549189.

• Miaoji Guo, JingJin*, Yong Jiao, Xingyu Wang, and Andrzej Cichocki, Investigation of Visual Stimulus With Various Colors and the Layout for the Oddball Paradigm in Evoked Related Potential-Based Brain-Computer Interface, Frontiers in Computational Neuroscience, 2019, 13: 24.

• Jiao Cheng, Jing Jin*, Ian Daly, Yu Zhang, Bei Wang, Xingyu Wang, and Andrzej Cichocki , Effect of a Combination of Flip and Zooming Stimuli on the Performance of a Visual Brain–Computer Interface for Spelling, Biomedical Engineering /Biomedizinische Technik, 2019, 64(1): 29-38.

• Jiankui Feng, Jing Jin*, Ian Daly, Jiale Zhou, Yugang Niu, Xingyu Wang, and Andrzej Cichocki, An Optimized Channel Selection Method Based on Multifrequency CSP-Rank for Motor Imagery-Based BCI System, Computational Intelligence and Neuroscience, 2019, 2019: 8068357.