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Outputs (3022)

Creating adapted environments: enhancing accessibility in virtual reality for upper limb rehabilitation through automated element adjustment (2025)
Journal Article
Herrera, V., Albusac, J., Castro-Schez, J. J., González-Morcillo, C., Monekosso, D. N., Pacheco, S., Perales, R., & de los Reyes-Guzmán, A. (2025). Creating adapted environments: enhancing accessibility in virtual reality for upper limb rehabilitation through automated element adjustment. Virtual Reality, 29, Article 28. https://doi.org/10.1007/s10055-024-01078-w

In the last decade, Virtual Reality (VR) has emerged as a promising tool for upper limb rehabilitation, effectively complementing conventional therapies. However, one of the main challenges lies in designing virtual environments that adapt to the spe... Read More about Creating adapted environments: enhancing accessibility in virtual reality for upper limb rehabilitation through automated element adjustment.

Introducing Code Quality at CS1 Level: Examples and Activities (2025)
Presentation / Conference Contribution
Izu, C., Mirolo, C., Börstler, J., Connamacher, H., Crosby, R., Glassey, R., Haldeman, G., Kiljunen, O., Kumar, A. N., Liu, D., Luxton-Reilly, A., Matsumoto, S., Carneiro De Oliveira, E., Russell, S., Shah, A., Izu, C., Mirolo, C., Börstler, J., Connamacher, H., Crosby, R., …Shah, A. (2024, July). Introducing Code Quality at CS1 Level: Examples and Activities. Presented at ITiCSE 2024: Innovation and Technology in Computer Science Education, Milan

Characterising code quality is a challenge that was addressed by a previous ITiCSE Working Group (Börstler et al., 2017). As emerged from that study, educators, developers, and students have different perceptions of the aspects involved. The percepti... Read More about Introducing Code Quality at CS1 Level: Examples and Activities.

The Complexity of Diameter on H-free Graphs (2025)
Presentation / Conference Contribution
Oostveen, J. J., Paulusma, D., & van Leeuwen, E. J. (2024, June). The Complexity of Diameter on H-free Graphs. Presented at WG 2024, Gozd Martuljek, Slovenia

Sparse Autoencoders Do Not Find Canonical Units of Analysis (2025)
Presentation / Conference Contribution
Leask, P., Bussmann, B., Pearce, M. T., Isaac Bloom, J., Tigges, C., Al Moubayed, N., Sharkey, L., & Nanda, N. (2025, April). Sparse Autoencoders Do Not Find Canonical Units of Analysis. Presented at The Thirteenth International Conference on Learning Representations, Singapore

A common goal of mechanistic interpretability is to decompose the activations of neural networks into features: interpretable properties of the input computed by the model. Sparse autoencoders (SAEs) are a popular method for finding these features in... Read More about Sparse Autoencoders Do Not Find Canonical Units of Analysis.

COPS: Controller Placement in Next-Generation Software Defined Edge-Cloud Networks (2025)
Presentation / Conference Contribution
Singh Aujla, G., Jindal, A., Kaur, K., Garg, S., Chaudhary, R., Sun, H., & Kumar, N. (2025, June). COPS: Controller Placement in Next-Generation Software Defined Edge-Cloud Networks. Presented at 2025 IEEE International Conference on Communications (ICC), Montreal, Canada

To mitigate various challenges in the edge-cloud ecosystem, such as global monitoring, flow control, and policy modification of legacy networking paradigms, software-defined networks (SDN) have evolved as a major technology. However, the dependency o... Read More about COPS: Controller Placement in Next-Generation Software Defined Edge-Cloud Networks.

Energy-based Predictive Root Cause Analysis for Real-Time Anomaly Detection in Big Data Systems (2025)
Presentation / Conference Contribution
Demirbaga, U., Singh Aujla, G., & Sun, H. (2025, June). Energy-based Predictive Root Cause Analysis for Real-Time Anomaly Detection in Big Data Systems. Presented at 2025 IEEE International Conference on Communications (ICC), Montreal, Canada

As the scale of data continues to grow exponentially, managing resource allocation and energy consumption in big data systems becomes increasingly complex and critical. Moreover, with big data systems, energy efficiency is more important daily. In cl... Read More about Energy-based Predictive Root Cause Analysis for Real-Time Anomaly Detection in Big Data Systems.

Generalising the maximum independent set algorithm via Boolean networks (2025)
Journal Article
Gadouleau, M., & Kutner, D. C. (2025). Generalising the maximum independent set algorithm via Boolean networks. Information and Computation, 303, Article 105266. https://doi.org/10.1016/j.ic.2025.105266

A simple greedy algorithm to find a maximal independent set (MIS) in a graph starts with the empty set and visits every vertex, adding it to the set if and only if none of its neighbours are already in the set. In this paper, we consider the generali... Read More about Generalising the maximum independent set algorithm via Boolean networks.