Outputs (13)

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.

Vortex generators in heat sinks: Design, optimisation, applications and future trends (2025)
Journal Article
Ismail, M., Ali, A. M., & Costa Pereira, S.-C. (2025). Vortex generators in heat sinks: Design, optimisation, applications and future trends. Results in Engineering, 25, Article 104216. https://doi.org/10.1016/j.rineng.2025.104216

Vortex generators (VGs) have been identified as an exceedingly effective method in augmenting heat transfer in minichannels, a significant feature of cutting-edge heat sinks, heat exchangers and electronics cooling tools. This paper aims to discuss t... Read More about Vortex generators in heat sinks: Design, optimisation, applications and future trends.

Enhancing Automotive Intrusion Detection Systems with Capability Hardware Enhanced RISC Instructions-Based Memory Protection (2025)
Journal Article
Kalutharage, C. S., Mohan, S., Liu, X., & Chrysoulas, C. (2025). Enhancing Automotive Intrusion Detection Systems with Capability Hardware Enhanced RISC Instructions-Based Memory Protection. Electronics, 14(3), 474. https://doi.org/10.3390/electronics14030474

The rapid integration of connected technologies in modern vehicles has introduced significant cybersecurity challenges, particularly in securing critical systems against advanced threats such as IP spoofing and rule manipulation. This study investiga... Read More about Enhancing Automotive Intrusion Detection Systems with Capability Hardware Enhanced RISC Instructions-Based Memory Protection.

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, https://doi.org/10.1080/10236198.2025.2461530

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.

Dynamic Caching Dependency-Aware Task Offloading in Mobile Edge Computing (2025)
Journal Article
Zhao, L., Zhao, Z., Hawbani, A., Liu, Z., Tan, Z., & Yu, K. (online). Dynamic Caching Dependency-Aware Task Offloading in Mobile Edge Computing. IEEE Transactions on Computers, https://doi.org/10.1109/TC.2025.3533091

Mobile Edge Computing (MEC) is a distributed computing paradigm that provides computing capabilities at the periphery of mobile cellular networks. This architecture empowers Mobile Users (MUs) to offload computation-intensive applications to large-sc... Read More about Dynamic Caching Dependency-Aware Task Offloading in Mobile Edge Computing.

Passivity theorems for input-to-state stability of forced Lur'e inclusions and equations, and consequent entrainment-type properties (2025)
Journal Article
Guiver, C. (online). 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, https://doi.org/10.1051/cocv/2025013

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. (2025). Neurosymbolic learning and domain knowledge-driven explainable AI for enhanced IoT network attack detection and response. Computers and Security, 151, Article 104318. 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.

Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model (2025)
Presentation / Conference Contribution
Renau, Q., & Hart, E. (2025, April). Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model. Presented at EvoSTAR 2025, Trieste, Italy

Recent approaches to training algorithm selectors in the black-box optimisation domain have advocated for the use of training data that is 'algorithm-centric' in order to encapsulate information about how an algorithm performs on an instance, rather... Read More about Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model.

Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing (2025)
Presentation / Conference Contribution
Sim, K., Hart, E., & Renau, Q. (2025, April). Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing. Presented at EvoSTAR 2025, Trieste, Italy

Coupling Large Language Models (LLMs) with Evolutionary Algorithms has recently shown significant promise as a technique to design new heuristics that outperform existing methods, particularly in the field of combinatorial optimisation. An escalating... Read More about Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing.

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.