Dr Muhammad Tariq Sadiq
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Email
m.t.sadiq@essex.ac.uk -
Location
5A.523, Colchester Campus
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Academic support hours
My Academic Support Hours will be 9:30–11:30 on Monday (in person) and 10:00–11:00 on Thursday (in person). The Zoom link for online meetings is available on my profile on the course MOODLE page. If you cannot visit my Support Hours due to other obligations please email me and we will arrange another time. Please feel free to drop me an email at m.t.sadiq@essex.ac.uk to discuss anything further.
Profile
Biography
With over 14 years of academic experience, I am an internationally recognised scholar in Artificial Intelligence (AI), Data Science, Machine Learning, Robotics, Control Engineering, and Biomedical Engineering, ranked among the World’s Top 2% Scientists (2022–2025). I hold a PhD in Pattern Recognition and Intelligent Systems, am a Chartered Engineer (CEng), Senior Member of IEEE (SMIEEE), Fellow of the Higher Education Academy (FHEA), and Member of the IET (MIET). I have been awarded the UK Global Talent Visa and now hold Indefinite Leave to Remain (ILR) in the UK. My research portfolio spans Explainable AI, Large Language Models (LLMs), Data Science, Brain–Computer Interfaces (BCIs), and Neurorobotics, with over 80 peer-reviewed publications (H-index: 33). I have secured over £212k in research funding, led major international collaborations across the UK–China, UK–Pakistan, and UK–Malaysia networks, and established a £100k Neurorobotics and Rehabilitation Laboratory. As a committed educator, I consistently achieve student satisfaction, design research-led and accredited programmes, and deliver innovative teaching in AI, Signal Processing, Machine Learning, and Digital Health. Alongside serving as Associate Editor and Guest Editor for leading journals, I champion interdisciplinary research that bridges Artificial Intelligence, Robotics, and Healthcare, driving real-world engineering and clinical impact.
Qualifications
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PhD Northwestern Polytechnical University, (2021)
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MSc Blekinge Institute of Technology, (2011)
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BSc COMSATS University Islamabad, (2009)
Appointments
University of Essex
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Lecturer (Assistant Professor), CSEE, University of Essex (1/3/2024 - present)
Other academic
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Lecturer, Robotics, Automation and Control Engineering, University of Brighton (26/8/2022 - 29/2/2024)
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Assistant Professor, Electrical Engineering, University of Lahore (1/3/2017 - 12/8/2022)
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Assistant Professor, Electrical Engineering, University of Engineering and Technology (Affiliated College: SCET) (5/1/2014 - 28/2/2017)
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Lecturer, Electrical Engineering, University of Engineering and Technology (Affiliated College: SCET) (5/2/2013 - 31/12/2013)
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Lecturer, Electrical Engineering, University of South Asia (5/2/2011 - 1/3/2013)
Research and professional activities
Research interests
Brain-computer interfacing
Development of new frameworks for motor imagery-based BCI systems.
Machine learning
To decipher intricate patterns and extract meaningful insights from complex data, enabling advancements in disease diagnosis, treatment optimization, and personalized healthcare.
EEG
Development of machine learning and signal processing algorithms for the development of novel frameworks for neural disease identification such as epilepsy, alzheimer's disease, parkinson's disease, depression, and schizophrenia.
Motor rehabilitation
Development of BCI systems to aid movement rehabilitation after injury or disease.
Analysis and Classification of Non-Stationary Signals
Development of signal processing and machine learning approaches for the development of automatic frameworks.
Teaching and supervision
Current teaching responsibilities
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Introduction to Databases (CE153)
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Brain-Computer Interfaces and Peripheral-Neural Interfaces (CE246)
Publications
Publications (1)
Lv, R., Akbari, H., Sadiq, MT., Chang, W. and Nawaz, R., From Segment-Level Discrimination to Unseen-Subject Transfer in Motor Imagery EEG: A Subject-Wise Study of a GAF–PLV Parallel CNN
Journal articles (11)
Azadnouran, A., Akbari, H., Sadiq, MT., Smith, D. and Mete, M., Comparative Evaluation of Time–Frequency Transformations and Pretrained CNN Models for EEG-Based Parkinson’s Disease Detection. BioMedInformatics. 6 (2), 12-12
Lv, R., Chang, W., Yan, G., Nie, W., Zheng, L., Guo, B. and Sadiq, MT., (2025). A novel recognition and classification approach for motor imagery based on spatio-temporal features. IEEE Journal of Biomedical and Health Informatics. 29 (1), 210-223
Yousaf, MZ., Guerrero, JM. and Sadiq, MT., (2025). Optimizing machine learning algorithms for fault classification in rolling bearings: A Bayesian Optimization approach. Engineering Applications of Artificial Intelligence. 150, 110597-110597
Lv, R., Chang, W., Yan, G., Sadiq, MT., Nie, W. and Zheng, L., (2025). Enhanced classification of motor imagery EEG signals using spatio-temporal representations. Information Sciences. 714, 122221-122221
Chang, W., Kong, W., Yan, G., Lv, R., Du, K., Sadiq, MT., Guo, B., Yin, R. and Liu, X., (2025). A multi-paradigm EEG dataset for studying upper limb rehabilitation exercises. Scientific Data. 12 (1), 1877-
Yousaf, MZ., Guerrero, JM., Sadiq, MT. and Farooq, U., (2025). Enhancing machinery reliability in lunar bases: Optimized machine learning for bearing fault classification in DC power distribution networks. Measurement. 253 (C), 117737-117737
Siuly, S., Tawhid, MNA., Li, Y., Acharya, R., Sadiq, MT. and Wang, H., (2025). Investigating Brain Lobe Biomarkers to Enhance Dementia Detection Using EEG Data. Cognitive Computation. 17 (2)
Siuly, S., Khare, SK., Kabir, E., Sadiq, MT. and Wang, H., (2024). An efficient Parkinson's disease detection framework: Leveraging time-frequency representation and AlexNet convolutional neural network.. Computers in Biology and Medicine. 174, 108462-108462
Yu, X., Aziz, MZ., Sadiq, MT., Jia, K., Fan, Z. and Xiao, G., (2022). Computerized Multidomain EEG Classification System: A New Paradigm. IEEE Journal of Biomedical and Health Informatics. 26 (8), 3626-3637
Akbari, H., Ghofrani, S., Zakalvand, P. and Tariq Sadiq, M., (2021). Schizophrenia recognition based on the phase space dynamic of EEG signals and graphical features. Biomedical Signal Processing and Control. 69, 102917-102917
Yu, X., Aziz, MZ., Sadiq, MT., Fan, Z. and Xiao, G., (2021). A New Framework for Automatic Detection of Motor and Mental Imagery EEG Signals for Robust BCI Systems. IEEE Transactions on Instrumentation and Measurement. 70, 1-12
Grants and funding
2024
Enhancing Motor Intention Decoding: A Cross-Cultural Approach
The Royal Society
Contact
Academic support hours:
My Academic Support Hours will be 9:30–11:30 on Monday (in person) and 10:00–11:00 on Thursday (in person). The Zoom link for online meetings is available on my profile on the course MOODLE page. If you cannot visit my Support Hours due to other obligations please email me and we will arrange another time. Please feel free to drop me an email at m.t.sadiq@essex.ac.uk to discuss anything further.