Mr Mahmoud Aldraimli


Mahmoud, A Quintin Hogg Trust scholar, began his career at the age of 20 in business management. After graduation, he worked with UK technology firms and corporations in process analysis, engineering, and systems development. In 2020, he joined the university as a Data Scientist Research Fellow, working on healthcare research with NHS Trusts, cancer centres, and academic institutions. Now a data science lecturer, Mahmoud’s research focuses on applied machine learning. Recently, he’s initiated machine learning projects with students and UK businesses in housing, healthcare, banking, construction, retail, and media. In 2024, Mahmoud was recognised for his excellence and nominated for a Go-Westminster Award. 


1- Aldraimli, M., Osman, S., Grishchuck, D., Ingram, S., Lyon, R., Mistry, A., Oliveira, J., Samuel, R., Shelley, L.E., Soria, D. and Dwek, M.V., 2022. Development and Optimization of a Machine- Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort. Advances in Radiation Oncology, 7(3), p.100890.

2- Aldraimli, M., Soria, D., Grishchuck, D., Ingram, S., Lyon, R., Mistry, A., Oliveira, J., Samuel, R., Shelley, L.E., Osman, S. and Dwek, M.V., 2021. A data science approach for early-stage prediction of Patient's susceptibility to acute side effects of advanced radiotherapy. Computers in biology and medicine, 135, p.104624.

3- Aldraimli, M., Nazyrova, N., Djumanov, A., Sobirov, I. and Chaussalet, T.J., 2020, October. A Comparative Machine Learning Modelling Approach for Patients’ Mortality Prediction in Hospital Intensive Care Unit. In The International Symposium on Bioinformatics and Biomedicine (pp. 16-31). Springer, Cham

4- Aldraimli, M., Soria, D., Parkinson, J., Thomas, E.L., Bell, J.D., Dwek, M.V. and Chaussalet, T.J., 2020. Machine learning prediction of susceptibility to visceral fat associated diseases. Health and Technology, 10(4), pp.925-944.

5- Aldraimli, M., Soria, D., Parkinson, J., Whitcher, B., Thomas, E.L., Bell, J.D., Chaussalet, T.J. and Dwek, M.V., 2019, September. Machine Learning Classification of Females Susceptibility to Visceral Fat Associated Diseases. In Mediterranean Conference on Medical and Biological Engineering and Computing (pp. 679-693). Springer, Cham.


  • Cyber security

Sustainable Development Goals
In brief

Research areas

A Quintin Hogg Trust scholar and a Go-Westminster Award nominee for 2024, was appointed in 2020 a Data Scientist Research Fellow, analysing healthcare records with machine learning alongside professionals from the NHS, cancer centers, and leading academic institutions across the globe. Today, as a lecturer in applied AI, Mahmoud inspires the next generation of innovators, guiding them in applying machine learning and deep learning to solve real-world challenges. His recent initiatives, collaborating with students and UK businesses across diverse sectors like housing, banking, construction, retail, and media, to shape the future of AI and its transformative impact on the industry.

Skills / expertise

Machine learning and Deep learning