Dr Junhua LI
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Email
junhua.li@essex.ac.uk -
Location
5A.535, Colchester Campus
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Academic support hours
Tuesdays 11 am - 12 noon and Wednesdays 1 pm - 2 pm. It would be great if you could let me know before coming. You are also welcome to make an appointment with me outside these time slots if needed.
Profile
Biography
He is a Senior Lecturer (Associate Professor) in the School of Computer Science and Electronic Engineering at the 糖心Vlog, UK. Before joining the 糖心Vlog, he was a Senior Research Fellow at the National University of Singapore, Singapore. He obtained a PhD in Computer Science from Shanghai Jiao Tong University, China. Given his background of computer science and computational neuroscience, he focuses on the research of brain-computer interface, neurophysiological signal processing, machine learning, and neuroimaging data analytics, as well as their practical applications. He is involved in a wide range of academic activities, such as Associate Editors of the IEEE Transactions on Artificial Intelligence (IEEE TAI), Medical & Biological Engineering & Computing, and IEEE Access. He is a Senior Member of the IEEE. It is now open to recruiting postgraduate research students (also known as PhD students). If you are interested in any of the research topics below and have funding to support your study, please get in touch with me for further discussions. (1) Developing machine learning algorithms (e.g., deep learning and tensor decomposition) for diverse applications (2) Brain-computer interface and health monitoring systems (3) Data analysis for understanding brain diseases and brain cognition Selected Publications (Last updated in 2020): -Tian Wang, Anastasios Bezerianos, Andrzej Cichocki, Junhua Li*, Multi-Kernel Capsule Network for Schizophrenia Identification, IEEE Transactions on Cybernetics, 2020, DOI: 10.1109/TCYB.2020.3035282 -Junhua Li*, Thoughts on Neurophysiological Signal Analysis and Classification, Brain Science Advances, 6(3), 210-223, 2020 -Junhua Li*, Nitish Thakor, Anastasios Bezerianos, Brain Functional Connectivity in Unconstrained Walking with and without An Exoskeleton, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(3), 730-739, 2020 -Jonathan Harvy, Nitish Thakor, Anastasios Bezerianos, Junhua Li*, Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(3), 358-367, 2019 -Junhua Li*, Rafael Romero-Garcia, John Sucking, Lei Feng*, Habitual Tea Drinking Modulates Brain Efficiency: Evidence from Brain Connectivity Evaluation, Aging, 11(11), 3876-3890, 2019 -Sim Kuan Goh, Hussein A. Abbass, Kay Chen Tan, Abdullah Al-Mamun, Nitish Thakor, Anastasios Bezerianos, Junhua Li*, Spatio-spectral Representation Learning for Electroencephalographic Gait-pattern Classification, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(9), 1858-1867, 2018 -Yu Sun, Julian Lim, Zhongxiang Dai, KianFoong Wong, Fumihiko Taya, Yu Chen, Junhua Li, Nitish Thakor, Anastasios Bezerianos, The Effects of A Mid-task Break on the Brain Connectome in Healthy Participants: A Resting-state Functional MRI Study, NeuroImage, 152, 19-30, 2017 -Junhua Li*, Chao Li, Andrzej Cichocki, Canonical Polyadic Decomposition with Auxiliary Information for Brain-Computer Interface, IEEE Journal of Biomedical and Health Informatics, 21(1), 263-271, 2017
Appointments
糖心Vlog
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Senior Lecturer, School of Computer Science and Electronic Engineering, 糖心Vlog (1/10/2023 - present)
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Lecturer, School of Computer Science and Electronic Engineering, 糖心Vlog (1/5/2019 - 30/9/2023)
Research and professional activities
Research interests
Machine Learning and Artificial Intelligence (Developing novel algorithms for classification and recognition; Detecting brain diseases based on neuroimaging data; Developing systems of monitoring human health)
To develop novel algorithms for pattern recognition and classification.
Computational Neuroscience (Understanding mechanisms of the brain pertaining to brain diseases, ageing, and mental states)
To analyse a wide range of data such as fMRI, TDI, EEG, EMG and PET and reveal neural mechanisms pertaining to cognition, emotion, and brain diseases.
Brain Health and Signal Processing (Providing insights into the brain health based on signals; Techniques for keeping the brain healthy and augmenting the brain capacity)
To investigate brain health-related issues based on signal processing and machine learning.
Teaching and supervision
Current teaching responsibilities
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Team Project Challenge (CE201)
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Neural Networks and Deep Learning (CE889)
Previous supervision
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 25/2/2025
Publications
Journal articles (55)
Sun, W. and Li, J., (2025). . IEEE Journal of Biomedical and Health Informatics. 29 (3), 1940-1949
Wang, H., Wang, Z., Sun, Y., Yuan, Z., Xu, T. and Li, J., (2024). . IEEE Transactions on Neural Systems and Rehabilitation Engineering. 32, 2270-2280
Lian, Z., Xu, T., Yuan, Z., Li, J., Thakor, N. and Wang, H., (2024). . IEEE Journal of Biomedical and Health Informatics. 28 (11), 6568-6580
Peng, Y., Liu, H., Li, J., Huang, J., Lu, B-L. and Kong, W., (2023). . IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, 759-768
Wang, Z., Chen, C., Li, J., Wan, F., Sun, Y. and Wang, H., (2023). . IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, 991-1000
Zhang, Y., Peng, Y., Li, J. and Kong, W., (2023). . Journal of Neuroscience Methods. 395, 109909-109909
Xu, T., Zhou, Z., Yang, Y., Li, Y., Li, J., Bezerianos, A. and Wang, H., (2023). . IEEE Access. 11, 65277-65288
Jin, F., Peng, Y., Qin, F., Li, J. and Kong, W., (2023). . Journal of King Saud University - Computer and Information Sciences. 35 (8), 101648-101648
Yu, Y., Bezerianos, A., Cichocki, A. and Li, J., (2023). . IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, 3417-3427
Zhu, L., Liu, Y., Liu, R., Peng, Y., Cao, J., Li, J. and Kong, W., (2023). . IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, 4683-4692
Gong, S., Xing, K., Cichocki, A. and Li, J., (2022). . IEEE Transactions on Cognitive and Developmental Systems. 14 (2), 348-365
Zhu, L., Cui, G., Li, Y., Zhang, J., Kong, W., Cichocki, A. and Li, J., (2022). . Cognitive Neurodynamics. 16 (4), 859-870
Duan, F., Lv, Y., Sun, Z. and Li, J., (2022). . Neural Processing Letters. 54 (3), 2455-2470
Wang, T., Bezerianos, A., Cichocki, A. and Li, J., (2022). . IEEE Transactions on Cybernetics. 52 (6), 4741-4750
Xu, T., Huang, J., Pei, Z., Chen, J., Li, J., Bezerianos, A., Thakor, N. and Wang, H., (2022). . IEEE Transactions on Biomedical Engineering. 70 (6), 1967-1978
Harvy, J., Bezerianos, A. and Li, J., (2022). . IEEE Transactions on Neural Systems and Rehabilitation Engineering. 30, 2743-2753
Wang, H., Liu, X., Li, J., Xu, T., Bezerianos, A., Sun, Y. and Wan, F., (2021). . IEEE Transactions on Cognitive and Developmental Systems. 13 (3), 668-678
Pei, Z., Wang, H., Bezerianos, A. and Li, J., (2021). . IEEE Transactions on Instrumentation and Measurement. 70, 1-8
Wang, H., Pei, Z., Xu, L., Xu, T., Bezerianos, A., Sun, Y. and Li, J., (2021). . IEEE Transactions on Instrumentation and Measurement. 70, 1-12
Li, J., (2021). . Frontiers in Neuroscience. 15, 652073-
Li, J., (2021). . Brain Science Advances. 6 (3), 210-223
Wei, C-S., Keller, CJ., Li, J., Lin, Y-P., Nakanishi, M., Wagner, J., Wu, W., Zhang, Y. and Jung, T-P., (2021). . Frontiers in Computational Neuroscience. 15, 791129-
Bose, R., Wang, H., Dragomir, A., Thakor, N., Bezerianos, A. and Li, J., (2020). . IEEE Transactions on Cognitive and Developmental Systems. 12 (2), 323-331
Wang, H., Tang, C., Xu, T., Li, T., Xu, L., Yue, H., Chen, P., Li, J. and Bezerianos, A., (2020). . IEEE Access. 8, 86850-86861
Wang, H., Xu, T., Tang, C., Yue, H., Chen, C., Xu, L., Pei, Z., Dong, J., Bezerianos, A. and Li, J., (2020). . IEEE Access. 8, 155590-155601
Zhu, L., Su, C., Zhang, J., Cui, G., Cichocki, A., Zhou, C. and Li, J., (2020). . Advanced Engineering Informatics. 46, 101191-101191
Li, J., Thakor, N. and Bezerianos, A., (2020). . IEEE Transactions on Neural Systems and Rehabilitation Engineering. 28 (3), 730-739
Feng, L., Romero-Garcia, R., Suckling, J., Tan, J., Larbi, A., Cheah, I., Wong, G., Tsakok, M., Lanskey, B., Lim, D., Li, J., Yang, J., Goh, B., Teck, TGC., Ho, A., Wang, X., Yu, J-T., Zhang, C., Tan, C., Chua, M., Li, J., Totman, JJ., Wong, C., Loh, M., Foo, R., Tan, CH., Goh, LG., Mahendran, R., Kennedy, BK. and Kua, E-H., (2020). . Aging. 12 (24), 24798-24816
Zhu, L., Zhou, C., Qu, Z. and Li, J., (2019). Monitoring time鈥恦arying residential load operation modes: an efficient signal disaggregation approach. IEEJ Transactions on Electrical and Electronic Engineering. 14 (1), 85-96
Li, J., Dimitrakopoulos, GN., Thangavel, P., Chen, G., Sun, Y., Guo, Z., Yu, H., Thakor, N. and Bezerianos, A., (2019). . IEEE Access. 7, 143935-143946
Bose, R., Goh, SK., Wong, KF., Thakor, N., Bezerianos, A. and Li, J., (2019). . Advanced Engineering Informatics. 42, 100992-100992
Li, J., Romero-Garcia, R., Suckling, J. and Feng, L., (2019). . Aging. 11 (11), 3876-3890
Harvy, J., Thakor, N., Bezerianos, A. and Li, J., (2019). . IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27 (3), 358-367
Li, J., Sun, Y., Huang, Y., Bezerianos, A. and Yu, R., (2019). Machine learning technique reveals intrinsic characteristics of schizophrenia: an alternative method. Brain Imaging and Behavior. 13 (5), 1386-1396
Li, J., Thakor, N. and Bezerianos, A., (2018). . Scientific Reports. 8 (1), 13470-
Wang, H., Dragomir, A., Abbasi, NI., Li, J., Thakor, NV. and Bezerianos, A., (2018). A novel real-time driving fatigue detection system based on wireless dry EEG. Cognitive Neurodynamics. 12 (4), 365-376
Yokota, T., Struzik, ZR., Jurica, P., Horiuchi, M., Hiroyama, S., Li, J., Takahara, Y., Ogawa, K., Nishitomi, K., Hasegawa, M. and Cichocki, A., (2018). Semi-Automated Biomarker Discovery from Pharmacodynamic Effects on EEG in ADHD Rodent Models. Scientific Reports. 8 (1), 5202-
Jurica, P., Struzik, ZR., Li, J., Horiuchi, M., Hiroyama, S., Takahara, Y., Nishitomi, K., Ogawa, K. and Cichocki, A., (2018). Combining behavior and EEG analysis for exploration of dynamic effects of ADHD treatment in animal models. Journal of Neuroscience Methods. 298, 24-32
Goh, SK., Abbass, HA., Tan, KC., Al-Mamun, A., Thakor, N., Bezerianos, A. and Li, J., (2018). . IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26 (9), 1858-1867
Sun, Y., Li, J., Suckling, J. and Feng, L., (2017). Asymmetry of Hemispheric Network Topology Reveals Dissociable Processes between Functional and Structural Brain Connectome in Community-Living Elders. Frontiers in Aging Neuroscience. 9 (NOV)
Dai, Z., de Souza, J., Lim, J., Ho, PM., Chen, Y., Li, J., Thakor, N., Bezerianos, A. and Sun, Y., (2017). EEG Cortical Connectivity Analysis of Working Memory Reveals Topological Reorganization in Theta and Alpha Bands. Frontiers in Human Neuroscience. 11
Li, J., Chen, Y., Taya, F., Lim, J., Wong, K., Sun, Y. and Bezerianos, A., (2017). A unified canonical correlation analysis-based framework for removing gradient artifact in concurrent EEG/fMRI recording and motion artifact in walking recording from EEG signal. Medical & Biological Engineering & Computing. 55 (9), 1669-1681
Sun, Y., Dai, Z., Li, J., Collinson, SL. and Sim, K., (2017). Modular鈥恖evel alterations of structure鈥揻unction coupling in schizophrenia connectome. Human Brain Mapping. 38 (4), 2008-2025
Ren, S., Li, J., Taya, F., deSouza, J., Thakor, NV. and Bezerianos, A., (2017). Dynamic Functional Segregation and Integration in Human Brain Network During Complex Tasks. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 25 (6), 547-556
Sun, Y., Lim, J., Dai, Z., Wong, K., Taya, F., Chen, Y., Li, J., Thakor, N. and Bezerianos, A., (2017). The effects of a mid-task break on the brain connectome in healthy participants: A resting-state functional MRI study. NeuroImage. 152, 19-30
Li, J., Li, C. and Cichocki, A., (2017). . IEEE Journal of Biomedical and Health Informatics. 21 (1), 263-271
Li, J., Lim, J., Chen, Y., Wong, K., Thakor, N., Bezerianos, A. and Sun, Y., (2016). Mid-Task Break Improves Global Integration of Functional Connectivity in Lower Alpha Band. Frontiers in Human Neuroscience. 10
Li, J., Wang, Y., Zhang, L., Cichocki, A. and Jung, T-P., (2016). Decoding EEG in Cognitive Tasks With Time-Frequency and Connectivity Masks. IEEE Transactions on Cognitive and Developmental Systems. 8 (4), 298-308
Bodala, IP., Li, J., Thakor, NV. and Al-Nashash, H., (2016). EEG and Eye Tracking Demonstrate Vigilance Enhancement with Challenge Integration. Frontiers in Human Neuroscience. 10
Dai, Z., Chen, Y., Li, J., Fam, J., Bezerianos, A. and Sun, Y., (2016). Temporal efficiency evaluation and small-worldness characterization in temporal networks. Scientific Reports. 6 (1)
Li, J., Struzik, Z., Zhang, L. and Cichocki, A., (2015). . Neurocomputing. 165, 23-31
Liu, Y., Li, M., Zhang, H., Wang, H., Li, J., Jia, J., Wu, Y. and Zhang, L., (2014). A tensor-based scheme for stroke patients鈥� motor imagery EEG analysis in BCI-FES rehabilitation training. Journal of Neuroscience Methods. 222, 238-249
LI, J., LIANG, J., ZHAO, Q., LI, JIE., HONG, KAN. and ZHANG, L., (2013). DESIGN OF ASSISTIVE WHEELCHAIR SYSTEM DIRECTLY STEERED BY HUMAN THOUGHTS. International Journal of Neural Systems. 23 (03), 1350013-1350013
Li, J. and Zhang, L., (2012). Active training paradigm for motor imagery BCI. Experimental Brain Research. 219 (2), 245-254
Li, J. and Zhang, L., (2010). Bilateral adaptation and neurofeedback for brain computer interface system. Journal of Neuroscience Methods. 193 (2), 373-379
Conferences (10)
Sun, W. and Li, J., (2024).
Wang, Z., Daly, I. and Li, J., (2023).
Wang, Z., Li, J., Daly, I. and Li, J., (2022).
Yu, Y. and Li, J., (2022).
Zian, P., Tao, X., Anastasios, B., Li, J., Yu, S. and Hongtao, W., (2020).
Harvy, J., Ewen, JB., Thakor, N., Bezerianos, A. and Li, J., (2019). Cortical Functional Connectivity during Praxis in Autism Spectrum Disorder
Harvy, J., Sigalas, E., Thakor, N., Bezerianos, A. and Li, J., (2018). Performance Improvement of Driving Fatigue Identification Based on Power Spectra and Connectivity Using Feature Level and Decision Level Fusions
He, J., Zhou, G., Wang, H., Sigalas, E., Thakor, N., Bezerianos, A. and Li, J., (2018). Boosting Transfer Learning Improves Performance of Driving Drowsiness Classification Using EEG
Sigalas, E., Li, J., Bezerianos, A. and Antonopoulos, CG., (2018).
Dimitrakopoulos, GN., Kakkos, I., Vrahatis, AG., Sgarbas, K., Li, J., Sun, Y. and Bezerianos, A., (2017). Driving Mental Fatigue Classification Based on Brain Functional Connectivity
Grants and funding
2024
Functional Connectivity Analysis of Biological Signals
Barrow Neurological Institute
2021
August International KTP 3 Application (2021)
Innovate UK (formerly Technology Strategy Board)
Contact
Academic support hours:
Tuesdays 11 am - 12 noon and Wednesdays 1 pm - 2 pm. It would be great if you could let me know before coming. You are also welcome to make an appointment with me outside these time slots if needed.
