Dr Amer Kareem
Dr Amer Kareem is a Lecturer in Computing at Northumbria University, with extensive experience in teaching, research and academic practice across higher education. He holds a PhD from the University of Bedfordshire, where he was awarded a Vice-Chancellor’s PhD Scholarship to support his doctoral research. He also holds an MSc in Computer Science from the University of Bedfordshire and a BSc (Hons) in Computer Science from Wrexham Glyndŵr University.
His research interests span Cloud Computing, Computer Networks, Artificial Intelligence, Machine Learning, Federated Learning, Cyber Security and Data Analytics. His research has particularly explored the application of machine learning and federated learning techniques to medical image analysis, including the detection of pneumonia from medical images.
Dr Kareem has published research in peer-reviewed academic journals, international conference proceedings and edited books. His publications cover a range of topics, including federated learning, medical image analysis, artificial intelligence, computer vision, blockchain security and cyber-physical systems.
Alongside his research, Dr Kareem has substantial experience in undergraduate and postgraduate teaching within Computing. At Northumbria University, he has undertaken module leadership and teaching across subjects including Computer Security, Big Data and Cloud Security, Cloud Computing and Business Processes. He is also actively involved in undergraduate and postgraduate project and dissertation supervision, assessment and moderation, academic quality assurance, curriculum development and supporting student academic development.
Key Publications
- Kareem, A., Liu, H. and Velisavljevic, V., 2023. A federated learning framework for pneumonia image detection using distributed data. Healthcare Analytics, p.100204.
- Nipun, M.S., Sulaiman, R.B. and Kareem, A., 2023. An Efficient Approach for Image Detection and Recognition Using Artificial Intelligence in Cyber-Physical Systems. In Computational Intelligence for Cybersecurity Management and Applications (pp. 101-119). CRC Press.
- Islam, M., Shuvo, S.A., Nipun, M.S., Bin Sulaiman, R., Shaikh, M.M., Nayeem, J., Haque, Z., Sourav, M.S.U. and Kareem, A., 2023. Efficient Approach to Using CNN-Based Pre-trained Models in Bangla Handwritten Digit Recognition. In Computational Vision and Bio-Inspired Computing: Proceedings of ICCVBIC 2022 (pp. 697-716). Singapore: Springer Nature Singapore.
- Arora, B., Jadhav, P., Sulaiman, R.B., Kareem, A., Kunekar, P. and Pant, B., 2022, December. Integrating Artificial Intelligence and Deep Learning for Enhanced Medical Innovation. In 2022 5th International Conference on Contemporary Computing and Informatics (IC3I) (pp. 327-331). IEEE.
- Kareem, A., Liu, H. & Sant, P. Review on Pneumonia Image Detection: A Machine Learning Approach. Hum-Cent Intell Syst 2, 31–43 (2022). https://doi.org/10.1007/s44230-022-00002-2
- A. Kareem and R. B. Sulaiman, “Applications of Blockchain Technology and Related Security Threats,” Security Engineering for Embedded and Cyber-Physical Systems, pp. 99–110, Jun. 2022, doi: 10.1201/9781003278207-7.
- R. Bin Sulaiman, A. Kareem, and M. U. Farooq, “Algorithms and Security Concern in Blockchain Technology,” Security Engineering for Embedded and Cyber-Physical Systems, pp. 3–24, Jun. 2022, doi: 10.1201/9781003278207-2.
- M. S. Nipun, R. B. Sulaiman, and A. Kareem, “Efficiency Comparison of AI classification algorithms for Image Detection and Recognition in Real-time,” arXiv:2206.05842 [cs], Jun. 2022, Accessed: Sep. 18, 2022. [Online]. Available: https://arxiv.org/abs/2206.05842
Academic Qualifications
- Ph.D. – University of Bedfordshire – 2020 – 2024
- MSc in Computer Science – University of Bedfordshire – 2018 – 2019
- BSc (Hons) in Computer Science – Glyndwr University – 2014 – 2017
Training and Certifications
- AWS (Solution Architect Associate)
- AWS (Certified Developer – Associate)
- CCNA (Cisco Certified Network Associate)
- Cisco (Certified Specialist – Enterprise Core)
- Cisco (Certified Specialist – Enterprise SD-WAN Implementation)
- CCNP (Cisco Certified Network Professional Enterprise)
- ML and Data Science: Zero to Mastery (Intensive 42 Hours Course)
