Dr Haider Raza
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Email
h.raza@essex.ac.uk -
Location
4B.528, Colchester Campus
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Academic support hours
My Academic Support Hour is 1:00 PM - 2:00 PM on Friday via zoom. The zoom link for this is available from my profile on my CE880/882 MOODLE page. Please wait in the waiting room until I can admit you.
Profile
Biography
I received the B.Tech. degree in Computer Science & Engineering from the Integral University, India, in 2008, the M.Tech. degree in Computer Engineering from the Manav Rachna International University, India, in 2011, and the PhD degree in computer science from University of Ulster University, Derry~Londonderry, U.K., in 2016. I worked as Postdoctoral Research Assistant at the University of Ulster in Neural Systems and Neuro-technology research team for EEG and MEG-based Brain-Computer Interfaces in 2016. Later, I joined as a Postdoctoral Research Officer in the Farr Institute of Health Informatics Research, Swansea University Medical School, U.K (2016-2017). From Nov-2017, I am working at the University of Essex.
Qualifications
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PhD University of Ulster, (2016)
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Master of Technology Manav Rachna International University, (2011)
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Bachelor of Technology Integral University, (2008)
Appointments
University of Essex
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Lecturer, School of Computer Science and Electronics Engineering, University of Essex (15/11/2020 - present)
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IADS Postdoctoral Research Fellow, School of Computer Science and Electronics Engineering, University of Essex (21/11/2017 - 14/11/2020)
Other academic
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Post-Doctorate Research Officer, Medical School, Swansea University (1/7/2016 - 20/11/2017)
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Research Assistant in Brain-Computer Interfacing, School of Computing and Intelligent Systems, University of Ulster (7/12/2015 - 30/6/2016)
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Visiting Researcher, Center of Mechantronics, Indian Institute of Technology Kanpur (6/4/2015 - 16/7/2015)
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Assistant Professor, School of Computer Science, Dilla University (3/10/2011 - 31/8/2012)
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Lecturer, Department of Information Technology, Manav Rachna International University (1/7/2009 - 30/9/2011)
Research and professional activities
Research interests
Big Data and Analytics
Brain-Computer Interface
Deep Learning
Transfer Learning
Non-Stationary Learning and Domain Adaptation
Artificial Intelligence (AI) and eXplainable AI (XAI)
EEG and MEG Signal Processing
AI in Decision Making for Healthcare
Teaching and supervision
Current teaching responsibilities
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Team Project Challenge (CE101)
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An Approachable Introduction to Data Science (CE880)
Current supervision
Publications
Journal articles (17)
Raza, H., Nara, S., Manuel, C. and Molinaro, N., Decoding Numeracy and Literacy in the Human Brain: Insights from MEG and MVPA. Scientific Reports
Roy, S., Gaur, V., Raza, H. and Jameel, S., (2023). CLEFT: Contextualised Unified Learning of User Engagement in Video Lectures with Feedback. IEEE Access. 11, 17707-17720
Singh, VK., Tripathi, G., Ojha, A., Bhardwaj, R. and Raza, H., (2023). Graph Laplacian for Heterogeneous Data Clustering in Sensor-Based Internet of Things. IETE Journal of Research, 1-13
Singh, VK., Singh, C. and Raza, H., (2022). Event Classification and Intensity Discrimination for Forest Fire Inference With IoT. IEEE Sensors Journal. 22 (9), 8869-8880
Raza, H., Rathee, D., Roy, S. and Prasad, G., (2021). A magnetoencephalography dataset for motor and cognitive imagery-based brain–computer interface. Scientific Data. 8 (1), 120-
Bhattacharyya, S., Konar, A., Raza, H. and Khasnobish, A., (2021). Editorial: Brain-Computer Interfaces for Perception, Learning, and Motor Control. Frontiers in Neuroscience. 15, 758104-
Raza, H., Rathee, D., Zhou, S-M., Cecotti, H. and Prasad, G., (2019). Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface. Neurocomputing. 343, 154-166
Chowdhury, A., Raza, H., Meena, YK., Dutta, A. and Prasad, G., (2019). An EEG-EMG Correlation-based Brain-Computer Interface for Hand Orthosis Supported Neuro-Rehabilitation. Journal of Neuroscience Methods. 312, 1-11
Raza, H., Zhou, S., Todd, S., Christian, D., Merchant, E., Morgan, K., Khanom, A., Hill, R., Lynos, R. and Brophy, S., (2019). Predictors of Objectively Measured Physical Activity in 12 month-Old Infants: A Study of Linked Birth Cohort Data with Electronic Health Records. Pediatric Obesity. 14 (7), e12512-e12512
Devi, SJ., Singh, B. and Raza, H., (2019). Link Prediction Evaluation Using Palette Weisfeiler-Lehman Graph Labelling Algorithm. International Journal of Knowledge and Systems Science. 10 (1), 1-20
Chowdhury, A., Raza, H., Meena, YK., Dutta, A. and Prasad, G., (2018). Online Covariate Shift Detection based Adaptive Brain-Computer Interface to Trigger Hand Exoskeleton Feedback for Neuro-Rehabilitation. IEEE Transactions on Cognitive and Developmental Systems. 10 (4), 1070-1080
Chowdhury, A., Meena, YK., Raza, H., Bhushan, B., Uttam, AK., Pandey, N., Hashmi, AA., Bajpai, A., Dutta, A. and Prasad, G., (2018). Active Physical Practice Followed by Mental Practice Using BCI-Driven Hand Exoskeleton: A Pilot Trial for Clinical Effectiveness and Usability. IEEE Journal of Biomedical and Health Informatics. 22 (6), 1786-1795
Raza, H., Zhou, S., Hill, R., Lyons, RA. and Brophy, S., (2017). Identification of predictors of objectively measured physical activity in 12-month-old British infants: a machine learning driven study. The Lancet. 390, S74-S74
Rathee, D., Raza, H., Prasad, G. and Cecotti, H., (2017). Current Source Density Estimation Enhances the Performance of Motor-Imagery-Related Brain–Computer Interface. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 25 (12), 2461-2471
Raza, H., Cecotti, H., Li, Y. and Prasad, G., (2016). Adaptive learning with covariate shift-detection for motor imagery-based brain–computer interface. Soft Computing. 20 (8), 3085-3096
Raza, H., Prasad, G. and Li, Y., (2015). EWMA model based shift-detection methods for detecting covariate shifts in non-stationary environments. Pattern Recognition. 48 (3), 659-669
Singh, B., Raza, H. and Ritu, M., (2010). GBG Approach for Connectivity and Coverage Control in Wireless Sensor Network. International Journal of Computer Applications. 16 (3), 13-18
Books (1)
Bhattacharyya, S., Konar, A., Raza, H. and Khasnobish, A., (2021). Brain-Computer Interfaces for Perception, Learning, and Motor Control. Frontiers Media SA. 2889718514. 9782889718511
Book chapters (2)
Liu, C., Raza, H. and Bhattacharyya, S., (2023). Deep learning methods for analysis of neural signals: From conventional neural network to graph neural network. In: Advanced Methods in Biomedical Signal Processing and Analysis. Elsevier. 205- 242. 9780323859554
Raza, H. and Rathee, D., (2018). Covariate shift detection-based nonstationary adaptation in motor-imagery-based brain–computer interface. In: Signal Processing and Machine Learning for Brain-Machine Interfaces. Editors: Tanaka, T. and Arvaneh, M., . Institution of Engineering and Technology. 125- 141. 9781785613982
Conferences (19)
Izwan Heroza, R., Raza, H. and Gan, J., SIA-SMOTE: A SMOTE-based Oversampling Method with Better Interpolation on High-Dimensional Data by Using a Siamese Network
Barry, E., Jameel, S. and Raza, H., (2022). Emojional: Emoji Embeddings
Raza, H., Chowdhury, A., Bhattacharyya, S. and Samothrakis, S., (2020). Single-Trial EEG Classification with EEGNet and Neural Structured Learning for Improving BCI Performance
Raza, H., Chowdhury, A. and Bhattacharyya, S., (2020). Deep Learning based Prediction of EEG Motor Imagery of Stroke Patients' for Neuro-Rehabilitation Application
Raza, H. and Samothrakis, S., (2019). Bagging Adversarial Neural Networks for Domain Adaptation in Non-Stationary EEG
Chowdhury, A., Raza, H., Dutta, A. and Prasad, G., (2017). EEG-EMG based Hybrid Brain Computer Interface for Triggering Hand Exoskeleton for Neuro-Rehabilitation
Raza, H., Cecotti, H. and Prasad, G., (2016). A combination of transductive and inductive learning for handling non-stationarities in motor imagery classification
Raza, H., Chowdhury, A., Dutta, A. and Prasad, G., (2015). Cortico-Muscular-Coupling and Covariate Shift Adaptation based BCI for Personalized Neuro- Rehabilitation of Stroke Patients
Raza, H., Cecotti, H., Li, Y. and Prasad, G., (2015). Learning with Covariate Shift-Detection and Adaptation in Non-Stationary Environments : Application to Brain-Computer Interface
Raza, H., Cecotti, H. and Prasad, G., (2015). Optimising Frequency Band Selection with Forward-Addition and Backward-Elimination Algorithms in EEG-based Brain-Computer Interfaces
Chowdhury, A., Raza, H., Dutta, A., Nishad, SS., Saxena, A. and Prasad, G., (2015). A Study on Cortico-muscular Coupling in Finger Motions for Exoskeleton Assisted Neuro-Rehabilitation
Raza, H., Prasad, G., Li, Y. and Cecotti, H., (2014). Covariate shift-adaptation using a transductive learning model for handling non-stationarity in EEG based brain-computer interfaces
Raza, H., Prasad, G., Li, Y. and Cecotti, H., (2014). Toward Transductive Learning Classifiers for Non-Stationary EEG
Raza, H., Prasad, G. and Li, Y., (2014). Adaptive Learning with Covariate Shift- Detection for Non-Stationary Environments
O Doherty, D., Meena, YK., Raza, H., Cecotti, H. and Prasad, G., (2014). Exploring gaze-motor imagery hybrid brain-computer interface design
Raza, H., Prasad, G. and Li, Y., (2014). Adaptive Learning with Covariate Shift-Detection for Non-Stationary Environments
Raza, H., Prasad, G. and Li, Y., (2013). Dataset shift detection in non-stationary environments using EWMA charts
Raza, H., Prasad, G. and Li, Y., (2013). EWMA based two-stage dataset shift-detection in non-stationary environments
Raza, H., Nandal, P. and Makker, S., (2010). Selection of cluster-head using PSO in CGSR protocol
Grants and funding
2022
Check4Cancer KTP Application (February 2022 submission).
Innovate UK (formerly Technology Strategy Board)
Brightstar Financial KTP Application - 2021 Submission
Innovate UK (formerly Technology Strategy Board)
2020
Unravelling the Forest Fires in Lower Himalayan Forests: A Comprehensive Study of Indian Forest Regions of Uttarakhand using IoT technology
University of Essex (GCRF)
Two-Way Visiting Fellowship with Indian colleague
University of Essex (GCRF)
Check4Cancer skin cancer AI model
Check4Cancer
Mersea Homes KTP application
Innovate UK (formerly Technology Strategy Board)
2019
The development of a new CPD tracker using AI and embedded machine learning to track and enhance performance of all staff.
Innovate UK (formerly Technology Strategy Board)
AI-Assisted Decision-Making System for Cancer Pathways of the Colchester Hospital
East Suffolk and North Essex NHS Foundation Trust
Maji - AI powered chatbot
Maji Financial Wellbeing Ltd
2018
Business and Local Government Data Research Centre (BLG DRC)
Economic and Social Research Council
Provide KTP 2018
Innovate UK (formerly Technology Strategy Board)
Contact
Academic support hours:
My Academic Support Hour is 1:00 PM - 2:00 PM on Friday via zoom. The zoom link for this is available from my profile on my CE880/882 MOODLE page. Please wait in the waiting room until I can admit you.