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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.

PEMS: Peoples Experience Of Mountain Soundscapes (2025)
Presentation / Conference Contribution
Donato, B. D., & Mcgregor, I. (2025, June). PEMS: Peoples Experience Of Mountain Soundscapes. Presented at Forum Acusticum / Euronoise 2025: 11th Convention of the European Acoustics Association, Málaga, Spain

This study investigates the role of soundscapes in mountain environments, focusing on their contributions to safety, navigation, and environmental understanding. A survey of 219 participants from 27 countries, primarily experienced mountaineers with... Read More about PEMS: Peoples Experience Of Mountain Soundscapes.

Scalable Machine Learning Architectures for IPA-Driven Maintenance Task Allocation in Large-Scale Building Portfolios (2025)
Presentation / Conference Contribution
Huang, Z., Liu, X., Romdhani, I., & Shih, C.-S. (2024, August). Scalable Machine Learning Architectures for IPA-Driven Maintenance Task Allocation in Large-Scale Building Portfolios. Presented at The 7th International Conference on Information Science and Systems (ICISS 2024), Edinburgh, UK

This research presents a groundbreaking approach to Building Maintenance Management (BMM) by introducing an Intelligent Process Automation (IPA)-Driven Building Maintenance Management (IBMM) model. This innovative model harnesses the synergies betwee... Read More about Scalable Machine Learning Architectures for IPA-Driven Maintenance Task Allocation in Large-Scale Building Portfolios.

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.

Computational Investigation of Laminar Premixed Hydrogen/Ammonia Flames at Sub-Atmospheric Conditions (2025)
Presentation / Conference Contribution
Tule, D., & Tingas, E.-A. (2025, January). Computational Investigation of Laminar Premixed Hydrogen/Ammonia Flames at Sub-Atmospheric Conditions. Presented at AIAA SCITECH 2025 Forum, Orlando, Florida

The increasing urgency to address global warming has highlighted the need to explore alternative fuels for the transport sector, a significant contributor to carbonemissions. Hydrogen and ammonia have emerged as promising candidates, each with distin... Read More about Computational Investigation of Laminar Premixed Hydrogen/Ammonia Flames at Sub-Atmospheric Conditions.

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.

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.

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.

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.

An investigation of the rotation patterns of international association meetings and events (2024)
Presentation / Conference Contribution
Drake, C., Lockstone-Binney, L., Robertson, M., & Thi Phuong Dung, L. (2024, February). An investigation of the rotation patterns of international association meetings and events. Presented at The 34th Annual Council for Australasian Tourism and Hospitality Education (CAUTHE) Conference, Hobart, Tasmania

International association meetings and events (IAMEs) are a significant segment of the business events sector. Noting the dearth of longitudinal research to confirm how these events rotate globally, regionally and over time, this study conducted an a... Read More about An investigation of the rotation patterns of international association meetings and events.

Integrating Reality: A Hybrid SDN Testbed for Enhanced Realism in Edge Computing Simulations (2024)
Presentation / Conference Contribution
Almaini, A., Koßmann, T., Folz, J., Schramm, M., Heigl, M., & Al-Dubai, A. (2024, June). Integrating Reality: A Hybrid SDN Testbed for Enhanced Realism in Edge Computing Simulations. Presented at UNet24: The International Conference on Ubiquitous Networking, Marrakesh, Morocco

Recent advancements in Software-Defined Networking (SDN) have facilitated its deployment across diverse network types, including edge networks. Given the broad applicability of SDN and the complexity of large-scale environments, establishing a compre... Read More about Integrating Reality: A Hybrid SDN Testbed for Enhanced Realism in Edge Computing Simulations.

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.

Beyond Hamming Distance: Exploring Spatial Encoding in Perceptual Hashes (2024)
Presentation / Conference Contribution
McKeown, S. (2025, April). Beyond Hamming Distance: Exploring Spatial Encoding in Perceptual Hashes. Presented at DFRWS EU 2025, Brno, Czech Republic

Forensic analysts are often tasked with analysing large volumes of data in modern investigations, and frequently make use of hashing technologies to identify previously encountered images. Perceptual hashes, which seek to model the semantic (visual)... Read More about Beyond Hamming Distance: Exploring Spatial Encoding in Perceptual Hashes.

A New Improved Method of Recurrent Memory Perception for Radar Echo Extrapolation (2024)
Presentation / Conference Contribution
Ji, R., Liu, Q., Zhang, Y., & Liu, X. (2024, July). A New Improved Method of Recurrent Memory Perception for Radar Echo Extrapolation. Presented at 2024 IEEE 24th International Conference on Software Quality, Reliability, and Security Companion (QRS-C), Cambridge, United Kingdom

Precipitation forecasting has long been a prominent topic in meteorology, as accurate predictions of impending rainfall are crucial for daily life and travel planning. Currently, radar echo extrapolation serves as the primary method for precipitation... Read More about A New Improved Method of Recurrent Memory Perception for Radar Echo Extrapolation.

FedCST: Federated Learning on Heterogeneous Resource-constrained Devices Using Clustering and Split Training (2024)
Presentation / Conference Contribution
Wang, Z., Lin, H., Liu, Q., Zhang, Y., & Liu, X. (2024, July). FedCST: Federated Learning on Heterogeneous Resource-constrained Devices Using Clustering and Split Training. Presented at The 24th International Conference on Software Quality, Reliability, and Security Companion (QRS-C), Cambridge, UK

With the rapid development of 5G and Internet of Things (IoT) technologies, edge devices such as sensors, smartphones, and wearable devices have become increasingly prevalent. The massive amount of distributed data generated by these devices offers u... Read More about FedCST: Federated Learning on Heterogeneous Resource-constrained Devices Using Clustering and Split Training.

High Intensity Radar Echo Extrapolation Based on Stacked Generative Structure (2024)
Presentation / Conference Contribution
Tao, S., Liu, Q., Zhang, Y., & Liu, X. (2024, July). High Intensity Radar Echo Extrapolation Based on Stacked Generative Structure. Presented at 2024 IEEE 24th International Conference on Software Quality, Reliability, and Security Companion (QRS-C), Cambridge, UK

In recent years, the phenomenon of severe convective disaster weather has increased significantly in the world. Due to the characteristics of small spatial scale, short occurrence period, great destructiveness and drastic changes, severe convective d... Read More about High Intensity Radar Echo Extrapolation Based on Stacked Generative Structure.

Applying the Right UX based on Users' Needs and Future Trends of UX (2024)
Presentation / Conference Contribution
Cameron, J. (2024, October). Applying the Right UX based on Users' Needs and Future Trends of UX. Presented at BINUS Business School International Lecture Week 2024, Jakarta, Indonesia and online

This lecture by Dr Jackie Cameron, an experienced digital marketing lecturer at Edinburgh Napier University, provides a comprehensive overview of user experience (UX) principles and their application in digital marketing contexts. Covering key defini... Read More about Applying the Right UX based on Users' Needs and Future Trends of UX.