Dr Junhua LI
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Email
junhua.li@essex.ac.uk -
Telephone
+44 (0) 1206 874012
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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 University of Essex, UK. Before joining the University of Essex, 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
University of Essex
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Senior Lecturer, School of Computer Science and Electronic Engineering, University of Essex (1/10/2023 - present)
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Lecturer, School of Computer Science and Electronic Engineering, University of Essex (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)
Current supervision
Publications
Journal articles (54)
Wang, H., Wang, Z., Sun, Y., Yuan, Z., Xu, T. and Li, J., (2024). A Cascade xDAWN EEGNet Structure for Unified Visual-evoked Related Potential Detection. 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). Driving Fatigue Detection Based on Hybrid Electroencephalography and Eye Tracking. IEEE Journal of Biomedical and Health Informatics, 1-12
Peng, Y., Liu, H., Li, J., Huang, J., Lu, B-L. and Kong, W., (2023). Cross-session Emotion Recognition by Joint Label-common and Label-specific EEG Features Exploration. 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). ST-CapsNet: Linking Spatial and Temporal Attention with Capsule Network for P300 Detection Improvement. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, 991-1000
Zhang, Y., Peng, Y., Li, J. and Kong, W., (2023). SIFIAE: An adaptive emotion recognition model with EEG feature-label inconsistency consideration.. Journal of Neuroscience Methods. 395, 109909-109909
Xu, T., Zhou, Z., Yang, Y., Li, Y., Li, J., Bezerianos, A. and Wang, H., (2023). Motor Imagery Decoding Enhancement Based on Hybrid EEG-fNIRS Signals. IEEE Access. 11, 65277-65288
Jin, F., Peng, Y., Qin, F., Li, J. and Kong, W., (2023). Graph adaptive semi-supervised discriminative subspace learning for EEG emotion recognition. Journal of King Saud University - Computer and Information Sciences. 35 (8), 101648-101648
Yu, Y., Bezerianos, A., Cichocki, A. and Li, J., (2023). Latent Space Coding Capsule Network for Mental Workload Classification. 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). Decoding Multi-Brain Motor Imagery From EEG Using Coupling Feature Extraction and Few-Shot Learning.. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, 4683-4692
Gong, S., Xing, K., Cichocki, A. and Li, J., (2022). Deep Learning in EEG: Advance of the Last Ten-Year Critical Period. 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). Attention allocation on mobile app interfaces when human interacts with them. Cognitive Neurodynamics. 16 (4), 859-870
Duan, F., Lv, Y., Sun, Z. and Li, J., (2022). Multi-Scale Learning for Multimodal Neurophysiological Signals: Gait Pattern Classification as An Example. Neural Processing Letters. 54 (3), 2455-2470
Wang, T., Bezerianos, A., Cichocki, A. and Li, J., (2022). Multi-Kernel Capsule Network for Schizophrenia Identification. 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). The Effect of Multiple Factors on Working Memory Capacities: Aging, Task difficulty, and Training. IEEE Transactions on Biomedical Engineering. 70 (6), 1967-1978
Harvy, J., Bezerianos, A. and Li, J., (2022). Reliability of EEG Measures in Driving Fatigue. 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). Driving Fatigue Recognition with Functional Connectivity Based on Phase Synchronization. IEEE Transactions on Cognitive and Developmental Systems. 13 (3), 668-678
Pei, Z., Wang, H., Bezerianos, A. and Li, J., (2021). EEG-Based Multi-Class Workload Identification Using Feature Fusion and Selection. 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). Performance Enhancement of P300 Detection by Multi-Scale-CNN. IEEE Transactions on Instrumentation and Measurement. 70, 1-12
Li, J., (2021). Editorial: Recent Developments of Deep Learning in Analyzing, Decoding, and Understanding Neuroimaging Signals. Frontiers in Neuroscience. 15, 652073-
Li, J., (2021). Thoughts on Neurophysiological Signal Analysis and Classification. 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). Editorial: Inter- and Intra-subject Variability in Brain Imaging and Decoding.. Frontiers in Computational Neuroscience. 15, 791129-
Bose, R., Wang, H., Dragomir, A., Thakor, N., Bezerianos, A. and Li, J., (2020). Regression Based Continuous Driving Fatigue Estimation: Towards Practical Implementation. 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). An Approach of One-vs-Rest Filter Bank Common Spatial Pattern and Spiking Neural Networks for Multiple Motor Imagery Decoding. 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). Diverse Feature Blend Based on Filter-Bank Common Spatial Pattern and Brain Functional Connectivity for Multiple Motor Imagery Detection. IEEE Access. 8, 155590-155601
Zhu, L., Su, C., Zhang, J., Cui, G., Cichocki, A., Zhou, C. and Li, J., (2020). EEG-based approach for recognizing human social emotion perception. Advanced Engineering Informatics. 46, 101191-101191
Li, J., Thakor, N. and Bezerianos, A., (2020). Brain functional connectivity in unconstrained walking with and without an exoskeleton. 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). Effects of choral singing versus health education on cognitive decline and aging: a randomized controlled trial. Aging. 12 (24), 24798-24816
Zhu, L., Zhou, C., Qu, Z. and Li, J., (2019). Monitoring time‐varying 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). What Are Spectral and Spatial Distributions of EEG-EMG Correlations in Overground Walking? An Exploratory Study. IEEE Access. 7, 143935-143946
Bose, R., Goh, SK., Wong, KF., Thakor, N., Bezerianos, A. and Li, J., (2019). Classification of Brain Signal (EEG) Induced by Shape-Analogous Letter Perception. Advanced Engineering Informatics. 42, 100992-100992
Li, J., Romero-Garcia, R., Suckling, J. and Feng, L., (2019). Habitual tea drinking modulates brain efficiency: evidence from brain connectivity evaluation. Aging. 11 (11), 3876-3890
Harvy, J., Thakor, N., Bezerianos, A. and Li, J., (2019). 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
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). Unilateral Exoskeleton Imposes Significantly Different Hemispherical Effect in Parietooccipital Region, but Not in Other Regions. 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). Spatio–Spectral Representation Learning for Electroencephalographic Gait-Pattern Classification. 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‐level alterations of structure–function 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). Canonical Polyadic Decomposition With Auxiliary Information for Brain–Computer Interface. 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). Feature learning from incomplete EEG with denoising autoencoder. 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’ 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., Deep Subdomain Adaptation Network Improves Cross-Subject Mental Workload Classification
Wang, Z., Daly, I. and Li, J., (2023). An Evaluation of Hybrid Deep Learning Models for Classifying Multiple Lower Limb Actions
Wang, Z., Li, J., Daly, I. and Li, J., (2022). Machine Learning for Multi-Action Classification of Lower Limbs for BCI
Yu, Y. and Li, J., (2022). Feature Fusion-Based Capsule Network for Cross-Subject Mental Workload Classification
Zian, P., Tao, X., Anastasios, B., Li, J., Yu, S. and Hongtao, W., (2020). The Effect of Longitudinal Training on Working Memory Capacities: An Exploratory EEG Study
Harvy, J., Ewen, JB., Thakor, N., Bezerianos, A. and Li, J., (2019). Cortical Functional Connectivity during Praxis in Autism Spectrum Disorder
Sigalas, E., Li, J., Bezerianos, A. and Antonopoulos, C., (2018). Emergence of chimera-like states in prefrontal-cortex macaque intracranial recordings
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
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
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.