Personal profile
Biography
Dr Rashid Kamal (PhD, FHEA) is a Lecturer in Computer Science at Ulster University, UK, where his research sits at the intersection in Secure AI, Generative AI, Artificial Intelligence, Digital Health, Pervasive Computing, and real-world AI applications. He received his PhD in Computer Science from Ulster University, where his research focused on Personalising and predicting notification breakpoints on mobile devices, funded by Invest Northern Ireland under the Connected Health Innovation Centre (CHIC) programme.
Dr Kamal has nearly a decade of teaching and research experience across the UK and internationally, previously serving as Lecturer at the University of Northampton and Abasyn University, and as a Visiting Lecturer at Ulster University. He has led and contributed to several funded research projects, including those supported by UKRI and industry partners, and has collaborated widely on applied AI solutions in healthcare, logistics, cybersecurity, and human–computer interaction.
His research has been recognised through multiple awards, including the People’s Award for Early Career Researcher (2024) at the University of Northampton, and Best Researcher Awards (2018–2020). He is also a Fellow of the Higher Education Academy (FHEA) and actively contributes to curriculum development, accreditation processes, and community outreach to promote diversity in computing.
Dr Kamal’s current research explores the security, robustness, and trustworthiness of AI systems, with a focus on adversarial resilience, multimodal learning, federated intelligence, and human-centred AI.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being
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SDG 4 Quality Education
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SDG 7 Affordable and Clean Energy
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SDG 8 Decent Work and Economic Growth
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 11 Sustainable Cities and Communities
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SDG 12 Responsible Consumption and Production
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SDG 17 Partnerships for the Goals
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Predicting Cryptocurrency Prices with ML-DL Models: A Hybrid Expert System Approach
Kamal, K., Mustafa, K., Kamal, R., Riaz, Y., Nugent, C., Jumani, F., Aslam, S. & Javaid, N., 1 Mar 2026, In: Expert Systems with Applications. 299, p. 1-19 19 p., 130114.Research output: Contribution to journal › Article › peer-review
Open AccessFile16 Downloads (Pure) -
Enhanced optimisation of MPLS network traffic using a novel adjustable Bat algorithm with loudness optimizer
Masood, M., Mostafa Fouad, M., Kamal, R., Aurangzeb, K., Aslam, S., Ullah, Z. & Glesk, I., 30 Jun 2025, In: Results in Engineering. 26, p. 1-15 15 p., 104774.Research output: Contribution to journal › Article › peer-review
Open AccessFile1 Link opens in a new tab Citation (Scopus)5 Downloads (Pure) -
Multi-Label Movie Genre Classification with Attention Mechanism on Movie Plots
Shaukat, F., Ejaz, N., Kamal, R., Alkhalifah, T., Aslam, S. & Mu, M., 19 May 2025, In: Computers, Materials & Continua. 83, 3, p. 5595-5622 28 p., 61702.Research output: Contribution to journal › Article › peer-review
Open AccessFile3 Link opens in a new tab Citations (Scopus)63 Downloads (Pure) -
Is identifying boredom the answer to controlling the bombardment of notifications on mobile devices?
Kamal, R., Rextin, A., Nugent, C., Cleland, I. & McCullagh, P., 1 Jun 2024, In: CCF Transactions on Pervasive Computing and Interaction. 6, 2, p. 115-132 18 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile44 Downloads (Pure) -
Addressing the inconsistent and missing time stamps in Nurse Care Activity Recognition Care Record Dataset
Kamal, R., Cleland, I., Nugent, C. & McCullagh, P., 29 Aug 2022, (Accepted/In press) Addressing the inconsistent and missing time stamps in Nurse Care Activity Recognition Care Record Dataset. Taylor & FrancisResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Thesis
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Personalising and predicting breakpoints for notifications on mobile devices
Kamal, R. (Author), Cleland, I. (Supervisor), Nugent, C. (Supervisor) & Mc Cullagh, P. (Supervisor), Jun 2024Student thesis: Doctoral Thesis
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