Dr Ateeq Ur Rehman is an Associate Professor of Computer Science in the Department of Computing at University of Staffordshire, with over 15 years of international academic experience across the UK, China, and South Asia. He has authored 50+ peer-reviewed journal articles and conference papers, with his work receiving over 1,750 citations.
His research focuses on the design of secure, privacy-aware, and trustworthy digital systems, particularly for healthcare, Industrial IoT, and other data-intensive and safety-critical environments. His work spans cyber security, data privacy, blockchain-based systems, and secure machine learning, with a strong emphasis on applied and deployable solutions.
Dr Rehman has led multiple Innovate UK–funded Knowledge Transfer Partnership projects, translating research into operational systems through close collaboration with industry partners. He actively supervises PhD, MSc, and undergraduate research students and contributes to interdisciplinary initiatives that bridge academic research, industrial innovation, and societal impact.
Dr Rehman welcomes research collaboration and expressions of interest from prospective PhD and MSc research students, postdoctoral researchers, and industry or funding partners, particularly in areas aligned with his current research interests.
Professional memberships and activities
- Senior Member, IEEE
- Fellow of the Higher Education Academy (FHEA)
Academic qualifications
- PhD in Computer Science, University of Southampton, UK
- Postgraduate Certificate in Higher and Professional Education, University of Staffordshire, UK
Expertise
- Cyber security and data privacy
- Secure and privacy-preserving machine learning
- Blockchain and distributed ledger technologies
- Internet of Things and Industrial IoT security
- Secure edge, fog, and cloud computing
- Healthcare and medical IoT systems
Research interests
- Data privacy and privacy-enhancing technologies
- Reliable Cyber security frameworks for healthcare and IoMT
- Blockchain-enabled trusted data systems
- Federated and secure machine learning
- Industrial IoT and cyber-physical system security
- Secure edge–cloud architectures
Grants
- Innovate UK Knowledge Transfer Partnership with Midlands Power Networks Ltd, led at the University of Staffordshire (£196,394)
- Innovate UK Knowledge Transfer Partnership with Currie Young Ltd, led at the University of Staffordshire (£195,475)
- UK Shared Prosperity Fund innovation projects delivered through the University of Staffordshire (completed)
Enterprise and commercial interests
- Innovate UK Knowledge Transfer Partnership projects with industry partners in collaboration with the University of Staffordshire
- Applied AI, data analytics, and secure digital platforms for enterprise and public-sector systems
- Industry-focused research translation and digital innovation
Teaching
Dr Rehman teaches and leads modules in computer science at University of Staffordshire, with a focus on critical systems application, Data Structure and Algorithms, Malware detection, Data Analytics, Secure mobile and software development. He supervises undergraduate, MSc, and PhD research projects and integrates industry case studies into teaching.
Publications
- T. Zhukabayeva, A. Ur Rehman, N. Tariq and E. Benkhelifa, "Hyperledger Fabric-Based Post Quantum Cryptography for Healthcare Application Using Discrete Event Simulation," in IEEE Access, vol. 12, pp. 192482-192493, 2024,
- Rehman, A. U. et al., IEEE Internet of Things Journal, 2024 – Privacy-preserving IoT and edge systems
- Rehman, A. U. et al., IEEE Transactions on Network Science and Engineering, 2024 – Blockchain-based healthcare systems
- Kanwal, F. Wahid, S. Ali, A. -U. Rehman, A. Alkhayyat and A. Al-Radaei, "Sentiment Analysis Using Hybrid Model of Stacked Auto-Encoder-Based Feature Extraction and Long
- Short Term Memory-Based Classification Approach," in IEEE Access, vol. 11, pp. 124181-124197, 2023
- Khan, F. et al., IEEE Transactions on Industrial Informatics, 2023 – Secure fog-cloud architectures for IoMT
- Rehman, A. U. et al., Future Generation Computer Systems, 2021 – Privacy-preserving mobile
For Detail and recent list, visit my Google Scholar Profile: https://scholar.google.com/citations?user=z1Ty5iQAAAAJ&hl=en