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The intersection of datafication and data justice in higher education (2025)
Presentation / Conference Contribution
Fabian, K. (2025, October). The intersection of datafication and data justice in higher education. Presented at Connecting Space, Data and Society: Interdisciplinary Pathways, London

There has been an increasing uptake of technology in the classroom, either for teaching or for classroom management purposes. Along with this uptake is the increasing datafication of education. Datafication is the process of rendering social and natu... Read More about The intersection of datafication and data justice in higher education.

Dynamic properties of a class of forced positive higher-order scalar difference equations: persistency, stability and convergence (2025)
Journal Article
Franco, D., Guiver, C., Logemann, H., & Perán, J. (in press). Dynamic properties of a class of forced positive higher-order scalar difference equations: persistency, stability and convergence. Journal of Difference Equations and Applications,

Persistency, stability and convergence properties are considered for a class of nonlinear, forced, positive, scalar higher-order difference equations. Sufficient conditions for these properties to hold are derived, broadly in terms of the interplay o... Read More about Dynamic properties of a class of forced positive higher-order scalar difference equations: persistency, stability and convergence.

Passivity theorems for input-to-state stability of forced Lur'e inclusions and equations, and consequent entrainment-type properties (2025)
Journal Article
Guiver, C. (in press). Passivity theorems for input-to-state stability of forced Lur'e inclusions and equations, and consequent entrainment-type properties. ESAIM: Control, Optimisation and Calculus of Variations,

A suite of input-to-state stability results are presented for a class of forced differential inclusions, so-called Lur’e inclusions. As a consequence, semi-global incremental input-to-state stability results for systems of forced Lur’e differential e... Read More about Passivity theorems for input-to-state stability of forced Lur'e inclusions and equations, and consequent entrainment-type properties.

Neurosymbolic learning and domain knowledge-driven explainable AI for enhanced IoT network attack detection and response (2025)
Journal Article
Kalutharage, C. S., Liu, X., & Chrysoulas, C. (online). Neurosymbolic learning and domain knowledge-driven explainable AI for enhanced IoT network attack detection and response. Computers and Security, https://doi.org/10.1016/j.cose.2025.104318

In the dynamic landscape of network security, where cyberattacks continuously evolve, robust and adaptive detection mechanisms are essential, particularly for safeguarding Internet of Things (IoT) networks. This paper introduces an advanced anomaly d... Read More about Neurosymbolic learning and domain knowledge-driven explainable AI for enhanced IoT network attack detection and response.

IoT Authentication Protocols: Challenges, and Comparative Analysis (2025)
Journal Article
Alsheavi, A., Hawbani, A., Othman, W., Wang, X., Qaid, G. R. S., Zhao, L., Al-Dubai, A., Liu, Z., Ismail, A., Haveri, R. H., Alsamhi, S. H., & Al-Qaness, M. A. A. (2025). IoT Authentication Protocols: Challenges, and Comparative Analysis. ACM computing surveys, 57(5), Article 116. https://doi.org/10.1145/3703444

In the ever-evolving information technology landscape, the Internet of Things (IoT) is a groundbreaking concept that bridges the physical and digital worlds. It is the backbone of an increasingly sophisticated interactive environment, yet it is a sub... Read More about IoT Authentication Protocols: Challenges, and Comparative Analysis.

A Multi-Tier Offloading Optimization Strategy for Consumer Electronics in Vehicular Edge Computing (2025)
Journal Article
Lin, H., Xiao, B., Zhou, X., Zhang, Y., & Liu, X. (2025). A Multi-Tier Offloading Optimization Strategy for Consumer Electronics in Vehicular Edge Computing. IEEE Transactions on Consumer Electronics, https://doi.org/10.1109/tce.2025.3527043

In the domain of consumer electronics, vehicular edge computing (VEC) technology is emerging as a novel data processing paradigm within vehicular networks. By sending tasks related to vehicular applications to the edge, this model makes it easier for... Read More about A Multi-Tier Offloading Optimization Strategy for Consumer Electronics in Vehicular Edge Computing.

An Evaluation of Domain-agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation (2025)
Presentation / Conference Contribution
Stone, C., Renau, Q., Miguel, I., & Hart, E. (2024, June). An Evaluation of Domain-agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation. Presented at 18th Learning and Intelligent Optimization Conference, Ischia, Italy

We address the question of multi-task algorithm selection in combinatorial optimisation domains. This is motivated by a desire to simplify the algorithm-selection pipeline by developing a more general classifier that does not require specialised info... Read More about An Evaluation of Domain-agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation.

Three ways to develop students’ AI literacy (2025)
Newspaper / Magazine
Gonsalves, C., & Illingworth, S. (2025). Three ways to develop students’ AI literacy

Is higher education prepared for a future defined by AI, or do we need to do more to align education with technology’s changing landscape? Here are three ways to get your students to engage with it critically.

Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode (2024)
Presentation / Conference Contribution
Buchanan, W., Grierson, S., & Uribe, D. (2024, February). Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode. Presented at 10th International Conference on Information Systems Security and Privacy, Rome, Italy

Biometric data is often highly sensitive, and a leak of this data can lead to serious privacy breaches. Some of the most sensitive of this type of data relates to the usage of DNA data on individuals. A leak of this type of data without consent could... Read More about Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode.

Library catalogue’s search interface: Making the most of subject metadata (2024)
Journal Article
Gnoli, C., Golub, K., Haynes, D., Salaba, A., Shiri, A., & Slavic, A. (2024). Library catalogue’s search interface: Making the most of subject metadata. Knowledge Organization, 51, 169-186. https://doi.org/10.5771/0943-7444-2024-3-169

This article addresses the underutilization of knowledge organization systems (KOS) elements in online library catalogues, hindering effective subject-based search and discovery. It highlights the International Society for Knowledge Organization's in... Read More about Library catalogue’s search interface: Making the most of subject metadata.

How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction (2024)
Presentation / Conference Contribution
Orme, M., Yu, Y., & Tan, Z. (2024, May). How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction. Presented at The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), Torino, Italy

This paper concerns the pressing need to understand and manage inappropriate language within the evolving human-robot interaction (HRI) landscape. As intelligent systems and robots transition from controlled laboratory settings to everyday households... Read More about How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction.

Convex neural network synthesis for robustness in the 1-norm (2024)
Presentation / Conference Contribution
Drummond, R., Guiver, C., & Turner, M. C. (2024, July). Convex neural network synthesis for robustness in the 1-norm. Presented at 6th Annual Learning for Dynamics & Control Conference, Oxford, England

With neural networks being used to control safety-critical systems, they increasingly have to be both accurate (in the sense of matching inputs to outputs) and robust. However, these two properties are often at odds with each other and a trade-off ha... Read More about Convex neural network synthesis for robustness in the 1-norm.

Exploring Dataset Diversity for GenAI Image Tampering Localisation in Digital Forensics (2024)
Presentation / Conference Contribution
Thomson, M., McKeown, S., Macfarlane, R., & Leimich, P. (2025, April). Exploring Dataset Diversity for GenAI Image Tampering Localisation in Digital Forensics. Presented at The Digital Forensics Research Conference Europe (DFRWS EU 2025) Digital Forensics Doctoral Symposium (DFDS), Brno, Czech Republic

Generative Artificial Intelligence (GenAI) has significantly increased the sophistication and ease of image tampering techniques, posing challenges for digital forensics in identifying manipulated images. A lack of dataset standardisation hinders the... Read More about Exploring Dataset Diversity for GenAI Image Tampering Localisation in Digital Forensics.

Becoming Rhizome: Deleuze and Guattari’s Rhizome as Theory and Method (2024)
Book Chapter
Drumm, L. (2024). Becoming Rhizome: Deleuze and Guattari’s Rhizome as Theory and Method. In Theory and Method in Higher Education Research: Volume 10 (37-55). Emerald. https://doi.org/10.1108/S2056-375220240000010003

This chapter explores Deleuze and Guattari’s rhizome as a multifaceted approach within educational research, suggesting it as an alternative way of mapping complexities, limiting structures and messiness which may not always be surfaced in more tradi... Read More about Becoming Rhizome: Deleuze and Guattari’s Rhizome as Theory and Method.

A True Random Number Generator Based On Race Hazard And Jitter Of Braided And Cross-Coupled Logic Gates Using FPGA (2024)
Journal Article
Ahmed, H. O., Kim, D., & Buchanan, B. (in press). A True Random Number Generator Based On Race Hazard And Jitter Of Braided And Cross-Coupled Logic Gates Using FPGA. IEEE Access, 12, 182943-182955. https://doi.org/10.1109/ACCESS.2024.3512419

In the contemporary digital landscape, security has become a vital element of our existence. The growing volume of sensitive information being stored and transmitted over networks necessitates the implementation of robust security measures. Cryptogra... Read More about A True Random Number Generator Based On Race Hazard And Jitter Of Braided And Cross-Coupled Logic Gates Using FPGA.

Editorial: Moving Artificial Intelligence Scholarship: Navigating the AI Frontier in Higher Education (2024)
Journal Article
Vahed, A., Reis, C., Singh, S., & Drumm, L. (2024). Editorial: Moving Artificial Intelligence Scholarship: Navigating the AI Frontier in Higher Education. African Journal of Inter/Multidisciplinary Studies, 6(1), 1-3. https://doi.org/10.51415/ajims.v6i1.1719

The swift and pervasive rise of artificial intelligence (AI), particularly Generative AI (GenAI), is reshaping the educational landscape globally. As we navigate a future shaped by developments in AI, the need for critical engagement, ethical framewo... Read More about Editorial: Moving Artificial Intelligence Scholarship: Navigating the AI Frontier in Higher Education.

Academic Staff AI Literacy Development Through LLM Prompt Training (2024)
Book Chapter
Drumm, L., & Sami, A. (2024). Academic Staff AI Literacy Development Through LLM Prompt Training. In X. O’Dea, & D. Tsz Kit Ng (Eds.), Effective Practices in AI Literacy Education: Case Studies and Reflections (41-49). Emerald. https://doi.org/10.1108/978-1-83608-852-320241005

A foundation in artificial intelligence (AI) literacy among all academic staff is essential for supporting students’ AI literacy effectively. As tools like ChatGPT increasingly influence academic work, educators need to understand prompt engineering... Read More about Academic Staff AI Literacy Development Through LLM Prompt Training.