Ossama Alshabrawy

Dr Ossama Alshabrawy

Assistant Professor

School: Computer Science

Ossama Alshabrawy is an assistant professor in the Department of Computer and Information Sciences. Ossama is interested in AI, Machine Learning/Deep Learning, Data Science, Computer Vision in particular around the domains of healthcare applications.

Ossama's most recent work focuses on the assessment of digital markers and causal treatment response evaluation from medical images for Head and Neck Cancer. Recently, Ossama is focusing analysing the social interactions of people with Depression in terms of analysing the speech and physical activities of the patients and extract digital markers from the data. He is also interested in analysing the acceleromter data of people with metabolic diseases especially Type-2 Diabetes and Cardiovascular disease.

Previously, Ossama was a research associate in the School of Computing, Newcastle University working on designing and assessment of deep learning networks and other machine learning models for predicting disease state from a combination of free-living movement data(accelerometry), trained over “Big Data” cohorts of individuals. Prior to that Ossama obtained his PhD degree in data science for healthcare from the School of Computing, Newcastle University.

Email Ossama

Research Themes and Scholarly Interests

AI, Causal Machine Learning/Deep Learning, Data Science, Medical imaging/Radiomics, Computer Vision, Digital Health, Wearable Computing

Key Publications

Causal Bio-miner: Response Biomarkers Discovery Framework for Microarray Transcriptomics Treatment Subgroups Classification, El-Nabawy, A., Alshabrawy, O., Woo, W. 22 Nov 2025, In: Expert Systems with Applications
Causal DNA Methylation Biomarkers Discovery Approach against Regression-based Latent Space of RNA to Protein Expression Translation Process, El-Nabawy, A., Alshabrawy, O., Woo, W. 7 Aug 2025, 2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), Piscataway, US, IEEE
Multimodal Deep Learning for Stage Classification of Head and Neck Cancer Using Masked Autoencoders and Vision Transformers with Attention-Based Fusion, Turki, A., Alshabrawy, O., Woo, W. 24 Jun 2025, In: Cancers
DNA Methylation Biomarkers Discovery Approach Using Weighted Causal Multi-Outcome Double Machine Learning Estimation, El-Nabawy, A., Alshabrawy, O., Woo, W. 23 Oct 2024, 2024 Sixth International Conference on Intelligent Computing in Data Sciences (ICDS), Piscataway, US, IEEE
Deep learning-based automated speech detection as a marker of social functioning in late-life depression, Little, B., Alshabrawy, O., Stow, D., Ferrier, I., McNaney, R., Jackson, D., Ladha, K., Ladha, C., Ploetz, T., Bacardit, J., Olivier, P., Gallagher, P., O'Brien, J. 1 Jul 2021, In: Psychological Medicine
Using Wearable Activity Trackers to Predict Type 2 Diabetes: Machine Learning–Based Cross-sectional Study of the UK Biobank Accelerometer Cohort, Lam, B., Catt, M., Cassidy, S., Bacardit, J., Darke, P., Butterfield, S., Alshabrawy, O., Trenell, M., Missier, P. 19 Mar 2021, In: JMIR Diabetes
Efficient Noisy Sound-Event Mixture Classification Using Adaptive-Sparse Complex-Valued Matrix Factorization and OvsO SVM, Parathai, P., Tengtrairat, N., Woo, W., Abdullah, M., Rafiee, G., Alshabrawy, O. 5 Aug 2020, In: Sensors
Blind separation of underdetermined mixtures with additive white and pink noises, Alshabrawy, O., Hassanien, A., Awad, W., Salama, A. 10 Oct 2014, 13th International Conference on Hybrid Intelligent Systems, HIS 2013, Piscataway, IEEE
Underdetermined Blind Separation of Mixtures of an Unknown Number of Sources with Additive White and Pink Noises, Alshabrawy, O., Hassanien, A. 2014, Proceedings of the 5th International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2014, Cham, Springer
Underdetermined blind separation of an unknown number of sources based on Fourier transform and Matrix Factorization, Alshabrawy, O., Ghoneim, M., Salama, A., Hassanien, A. 1 Dec 2013, 2013 Federated Conference on Computer Science and Information Systems, FedCSIS 2013, Piscataway, IEEE

PGR Supervision

Alaa Elnabawy Biomarkers Discovery Framework based On Discriminant Analysis and Causal Inference Start Date: 01/12/2022
Ahmed Karam Deep Learning for Brain Tumor Identification Start Date: 01/03/2023