Personal profile

Academic Biography

My Academic and professional training is in computer science in which I have received a bachelor’s degree, MSc and PhD. My PhD research is within the domain of using data science and artificial intelligence approaches to analyse data to help in the predictive diagnosis of lumbar spine disease by automating the manual techniques used by clinicians. In particular, I performed complex data analysis and feature extractions to predict lumbar spine diseases. The methods I have developed are not limited to analysing one disease; as such approaches lend themselves to other data-intensive domains within and outside the medical setting.


I have a strong academic background and more than 16 years of university teaching experience in addition to my technical expertise in using multiple programming languages such as Java, C, and C++, and having high knowledge in using Matlab and working in different machine learning approaches like support vector machine SVM, convolutional neural networks and deep neural networks. 

In teaching, I'm working as a senior computer science lecturer at Teesside University to be involved in teaching and developing computer science modules at the department. In my previous experience, I worked as a sessional lecturer at LJMU delivering lectures and lab tutorials for a variety of modules such as (Introduction to Programming, Computer Systems, Data Science and Analytics, Advanced Software Development, Contemporary Software Development, Software Engineering Workshop, Knowledge-Based System, Algorithms and Computing, and Research Skills). Regarding my previous experience, I was a lecturer at many international universities in Dubai, Sultanate of Oman and Jordan teaching different subjects following the organizations' policy and teaching standards. Moreover, I was the module leader for a variety of modules and part of my duties was module development which included the teaching materials, exam preparations, technology used in teaching and curriculum review. Working with other team members was also part of the duties to improve the course outcome. My primary aim was to make the subject more interesting and effective for the students. I changed some assessment methods throughout teaching the subject, reviewed and introduced questions for short quizzes, adopted exciting practical activities that illustrate visual understanding and open the topics for discussions, gave pair and group work assignments, and revised the whole final examination paper, focusing on knowledge of topic sought to bring out students’ understanding. I strived to encourage the deep understanding approach to learning where the emphasis is on the subject’s relevance and application, rather than acquired facts and history they had just memorized. The deep approach seeks to make sense of what is learned, combines knowledge and theoretical ideas to everyday experience, and is characterised by the relation of and reflection on past knowledge to new and modern knowledge. The significant aims of this method are strengthening students' ability to use their energies of imagination, to be flexible, to reflect, to adapt and transfer skills, and to use this understanding in innovative ways. As a part of my professional development, I have done the PGCert (Postgraduate Certificate in Academic Practice) to reach a nationally recognised standard of higher education teaching and learning support in addition to exploring a range of methods and approaches to enhance my skills. 

I make it my goal to instil ideas and knowledge from the students instead of ‘spoon-feeding’ them. I endeavour to ask relevant questions and provide activities geared toward reflective learning. Small group discussions and relevant workshops provide quite an efficient learning environment and encourage students to participate, particularly between quiet and shy students. Students’ collaboration and team activities make the subject more exciting and help in preserving students’ concerns. An environment that provides opportunities for the students to participate and get involved is essential in the learning process. 

In my previous role as a Postdoctoral Research Associate in Statistical Methodology Development, I acted as the mathematical and statistical developer for the project. I combine cutting-edge statistical learning and machine learning methods to quantify uncertainty and propose mathematical solutions that will underpin the decision support system, test the system, run simulations, and develop strategies for dynamic updating of the system. In my previous job as a data analyst and programming consultant, I utilised data analytics techniques to analyse data from trains and tracks to investigate the situation where slippery rail can be detected, the correlation between slippery rail and current mitigations, and optimal plans for mitigation. Moreover, I combine the analysed data with the data previously developed by LJMU in another project to deliver a pilot/simulation that can be further developed into a future system for the industry. 

As a part of my PhD research, I have been engaged in a research project collaboration with academic and non-academic staff involving my base unit at Liverpool John Moores University (LJMU) and external partners. Most notably, a collaborative project with the University Multimedia Nusantara, Jakarta, Indonesia funded by PKLN from the Indonesian Ministry of Research and Higher Education aimed at developing an analytical tool for Predicting lumbar spine diseases. The tool is targeted by radiologists and orthopedists. We have published a journal paper to report our findings.

In summary, I have a professional attitude to work and I am always keen to develop new skills. I always strive to make a difference and leave a positive legacy wherever I find myself. I am confident that those I have worked with will have nothing but a good appraisal of me.


Education/Academic qualification

PhD, A Machine Learning Approach to Computer Assisted Diagnosis of Chronic Lower Back Pain on Lumbar Spine Magnetic Resonance Images, Liverpool John Moores University

Award Date: 1 Oct 2019

Master, New York Institute of Technology

Award Date: 4 Aug 2005


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