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Muhammad Azeem Abbas PhD

Programme Manager — BSc (Hons) Applied Computing, BSc (Hons) Cloud Computing and CertHE Computing Skills for the Workplace

 

E-mail: m.abbas@uwtsd.ac.uk



Programme Manager — BSc (Hons) Applied Computing, BSc (Hons) Cloud Computing and CertHE Computing Skills for the Workplace.

Muhammad Azeem Abbas is a highly skilled artificial intelligence/machine learning professional having both industrial and academic experience. Before UWTSD, he was working as a Research Officer on industry-led projects at Leeds Beckett University (LBU) and as an Assistant Professor at a university. As a faculty member, he has taught both core and elective courses of computer science and information technology degree programmes at undergraduate and postgraduate level.

He has completed three research projects as a principal investigator that were funded by national and international funding agencies. He was a lead member of the team responsible for drafting the proposals for the establishment of national research centres at the agriculture university.

In addition to teaching and research, Dr. Abbas is a passionate programmer with software development experience in both the public and private sectors. During his career as a software engineer, he has developed several enterprise and commercial software projects. His software development expertise is in C/C++, Python (TensorFlow and PyTorch), full-stack development, .Net framework and Node.js.

Dr. Abbas is serving as an editorial member of the Computer and Education: Artificial Intelligence journal (Elsevier).

Dr. Abbas’s research focus is Artificial Intelligence (AI); more specifically, the application of AI and machine learning in education, health, and industrial operations. He has recently published several applied research contributions in the field of artificial intelligence in education and health. Two PhD and more than ten Master’s students have completed their research dissertation under his supervision.

Oyegoke, Adekunle; Ajayi, Saheed; Abbas, Muhammad; Ogunlana, Stephen. (2022). Development of Adapt-able Smart System – An end-to-end system for speeding up disabled housing adaptation process. International Journal of Building Pathology and Adaptation [Accepted]

Fazal Z., Khan, S., Abbas, M. A., Shahzad, Younis., (2021). Machine Learning Approach for Prediction of Crimp in Cotton Woven Fabrics, Journal of Technical Gazette. Vol 28 (1). February 2021.

Siddiquah, A., Khan, S., Abbas, M. A., & Ajayi, S. (2021). Usage Patterns and Effects of Mobile Learning Activities Using Social Learning Apps on the Achievement of Undergraduate Students in a History of Art Course. International Journal of Mobile Learning and Organisation.

Abbas, M. A., Hammad, S., Hwang, G.-J., Khan, S., & Gilani, S. M. M. (2020). An assistive environment for EAL academic writing using formulaic sequences classification. Interactive Learning Environments, 0(0), 1–15. https://doi.org/10.1080/10494820.2020.1789670

Parveen, N., Khan, S., Shah, Saeed., Abbas, M. A., Shahzad, Younis., & Kinza S. (2020). Development of a cost-effective CVD prediction model using lifestyle factors. A cohort study in Pakistan. Journal of African Health Sciences, Vol 20 (2), June 2020.

Mustafa, G., Abbas, M. A., Hafeez, Y., Khan, S., & Hwang, G.-J. (2019). Effectiveness of ontology-based learning content generation for preschool cognitive skills learning. Interactive Learning Environments, 27(4), 443–457.

Rehman, T., Khan, S., Hwang, G.-J., & Abbas, M. A. (2019). Automatically solving two-variable linear algebraic word problems using text mining. Expert Systems, 36(2), e12358.

Sharifullah, K., Gwo-Jen, H., Muhammad Azeem, A., & Arshia, R. (2019). Mitigating the urban--rural educational gap in developing countries through mobile technology-supported learning. British Journal of Educational Technology, 50(2), 735–749.

Sultana, S., Khan, S., & Abbas, M. A. (2017). Predicting performance of electrical engineering students using cognitive and non-cognitive features for identification of potential dropouts. International Journal of Electrical Engineering Education, 54(2), 105–118.

Syed Mushhad Mustuzhar Gilani Tang Hong, Guofeng Zhao Chuan, X., & Abbas, M. A. (2019). An Empirical Throughput Analysis of Multimedia Applications with OpenFlow-based Dynamic Load Balancing Approach in WLAN. Journal of Internet Technology, 20(1), 237–246.

Rabia Irfan, Sharifullah Khan,  Muhammad Azeem Abbas, Asad Ali Shah. (2019). Determining influential factors and challenges in automatic taxonomy generation. Information Research: an international electronic journal. 24(2), 822.

Shoaib, L., Khan, S., Abbas, M. A., & Salman, A. (2018). Enabling profound hearing impaired children to articulate words using lip-reading through software application. Journal of the Pakistan Medical Association, 68(3).

Jilani, M. T., Rehman, M. Z. U., Khan, A. M., Chughtai, O., Abbas, M. A., & Khan, M. T. (2018). An implementation of IoT-based microwave sensing system for the evaluation of tissues moisture. Microelectronics Journal.

Khan, S. A., Qadir, M. A., Abbas, M. A., & Afzal, M. T. (2017). OWL2 benchmarking for the evaluation of knowledge based systems. PLoS ONE, 12(6).

Abbas, M. A., Ahmad, W. F. W., & Kalid, K. S. (2014). Semantic Web Technologies for Pre-School Cognitive Skills Tutoring System. Journal of Information Science and Engineering, 30(3), 835–851.

Abbas, M. A., Qadir, A., Ahmad, M., & Ali, T. (2012). Satisfiability and Implication Evaluation of Conjunctive Queries in Semantic Caching. Journal of E-Technology, 3(3), 133–143.