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All Outputs (1325)

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.

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.

Calculating the Capacity Region of a Quantum Switch (2025)
Presentation / Conference Contribution
Tillman, I., Vasantam, T., Towsley, D., & Seshadreesan, K. P. (2024, September). Calculating the Capacity Region of a Quantum Switch. Presented at QCE2024: IEEE International Conference on Quantum Computing and Engineering, Montréal, Québec, Canada

Quantum repeaters are necessary to fully realize the capabilities of the emerging quantum internet, especially applications involving distributing entanglement across long distances. A more general notion of this can be called a quantum switch, which... Read More about Calculating the Capacity Region of a Quantum Switch.

An on-demand resource allocation algorithm for a quantum network hub and its performance analysis (2025)
Presentation / Conference Contribution
Gauthier, S., Vasantam, T., & Vardoyan, G. (2024, September). An on-demand resource allocation algorithm for a quantum network hub and its performance analysis. Presented at QCE24: IEEE International Conference on Quantum Computing and Engineering, Montréal, Québec, Canada

To support the execution of multiple simultaneously-running quantum network applications, a quantum network must efficiently allocate shared resources. We study traffic models for a type of quantum network hub called an Entanglement Generation Switch... Read More about An on-demand resource allocation algorithm for a quantum network hub and its performance analysis.

Fully-Automated Patient-Agnostic Diabetes Management with Deep Reinforcement Learning (2025)
Presentation / Conference Contribution
Milton, T., & Lieck, R. (2024, December). Fully-Automated Patient-Agnostic Diabetes Management with Deep Reinforcement Learning. Presented at 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Lisbon, Portugal

Type 1 diabetes is a chronic metabolic disease that requires regular insulin injections to regulate blood glucose levels. Recently, traditional manual approaches to diabetes management have been revolutionized by the use of continuous glucose monitor... Read More about Fully-Automated Patient-Agnostic Diabetes Management with Deep Reinforcement Learning.

SYCL compute kernels for ExaHyPE (2024)
Presentation / Conference Contribution
Loi, C. M., Bockhorst, H., & Weinzierl, T. (2024, March). SYCL compute kernels for ExaHyPE. Presented at 2024 SIAM Conference on Parallel Processing for Scientific Computing (PP), Baltimore, MD

We discuss three SYCL realisations of a simple Finite Volume scheme over multiple Cartesian patches. The realisation flavours differ in the way how they map the compute steps onto loops and tasks: We compare an implementation that is exclusively usin... Read More about SYCL compute kernels for ExaHyPE.

Predator-Prey Q-Learning Based Collaborative Coverage Path Planning for Swarm Robotics ⋆ (2024)
Presentation / Conference Contribution
Watson, M., Ren, H., Arvin, F., & Hu, J. (2024, August). Predator-Prey Q-Learning Based Collaborative Coverage Path Planning for Swarm Robotics ⋆. Presented at 2024 Annual Conference Towards Autonomous Robotic Systems (TAROS), London

Coverage Path Planning (CPP) is an effective approach to let intelligent robots cover an area by finding feasible paths through the environment. In this paper, we focus on using reinforcement learning to learn about a given environment and find the m... Read More about Predator-Prey Q-Learning Based Collaborative Coverage Path Planning for Swarm Robotics ⋆.

The threshold of existence of δ-temporal cliques in random simple temporal graphs (2024)
Presentation / Conference Contribution
Mertzios, G. B., Nikoletseas, S., Raptopoulos, C., & Spirakis, P. (2024, September). The threshold of existence of δ-temporal cliques in random simple temporal graphs. Presented at The 20th International Symposium on Algorithmics of Wireless Networks (ALGOWIN), Egham, London, United Kingdom

Reconfigurable routing in data center networks (2024)
Presentation / Conference Contribution
Kutner, D. C., & Stewart, I. A. (2024, September). Reconfigurable routing in data center networks. Presented at 20th International Symposium on Algorithmics of Wireless Networks, ALGOWIN 2024, Egham, UK

A hybrid network is a static (electronic) network that is augmented with optical switches. The Reconfigurable Routing Problem (RRP) in hybrid networks is the problem of finding settings for the optical switches augmenting a static network so as to ac... Read More about Reconfigurable routing in data center networks.

Interactive Digital Storytelling Navigating the Inherent Currents of the Diasporic Mind (2024)
Presentation / Conference Contribution
Nisi, V., Bala, P., Pessoa, M., James, S., & Nunes, N. (2024, December). Interactive Digital Storytelling Navigating the Inherent Currents of the Diasporic Mind. Presented at International Conference on Interactive Digital Storytelling (ICIDS 2024), Barranquilla, Colombia

Due to a recent increase in conflicts, natural disasters, and economic crises, a growing wave of migrant populations has been searching for asylum in Europe. For this population of asylum seekers, the migration process, like currents and rapids, can... Read More about Interactive Digital Storytelling Navigating the Inherent Currents of the Diasporic Mind.

Beyond Syntax: How Do LLMs Understand Code? (2024)
Presentation / Conference Contribution
North, M., Atapour-Abarghouei, A., & Bencomo, N. (2025, April). Beyond Syntax: How Do LLMs Understand Code?. Presented at 2025 IEEE/ACM International Conference on Software Engineering ICSE, Ottawa , Canada

Within software engineering research, Large Language Models (LLMs) are often treated as 'black boxes', with only their inputs and outputs being considered. In this paper, we take a machine interpretability approach to examine how LLMs internally repr... Read More about Beyond Syntax: How Do LLMs Understand Code?.

Block Ciphers in Idealized Models: Automated Proofs and New Security Results (2024)
Presentation / Conference Contribution
Ambrona, M., Farshim, P., & Harasser, P. (2024, October). Block Ciphers in Idealized Models: Automated Proofs and New Security Results. Presented at ACM SIGSAC Conference on Computer and Communications Security 2024, Salt Lake City, USA

We develop and implement AlgoROM, a tool to systematically analyze the security of a wide class of symmetric primitives in idealized models of computation. The schemes that we consider are those that can be expressed over an alphabet consisting of XO... Read More about Block Ciphers in Idealized Models: Automated Proofs and New Security Results.

Neural-code PIFu: High-fidelity Single Image 3D Human Reconstruction via Neural Code Integration (2024)
Presentation / Conference Contribution
Liu, R., Remagnino, P., & Shum, H. P. (2024, December). Neural-code PIFu: High-fidelity Single Image 3D Human Reconstruction via Neural Code Integration. Presented at 2024 International Conference on Pattern Recognition, Kolkata, India

We introduce neural-code PIFu, a novel implicit function for 3D human reconstruction, leveraging neural codebooks, our approach learns recurrent patterns in the feature space and reuses them to improve current features. Many existing methods predict... Read More about Neural-code PIFu: High-fidelity Single Image 3D Human Reconstruction via Neural Code Integration.

Complexity framework for forbidden subgraphs II: Edge subdivision and the "H"-graphs (2024)
Presentation / Conference Contribution
Lozin, V. V., Martin, B., Pandey, S., Paulusma, D., Siggers, M., Smith, S., & van Leeuwen, E. J. (2024, December). Complexity framework for forbidden subgraphs II: Edge subdivision and the "H"-graphs. Presented at ISAAC, ISAAC 2024

For a fixed set H of graphs, a graph G is H-subgraph-free if G does not contain any H ∈ H as a (not necessarily induced) subgraph. A recent framework gives a complete classification on H-subgraph-free graphs (for finite sets H) for problems that are... Read More about Complexity framework for forbidden subgraphs II: Edge subdivision and the "H"-graphs.

From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos (2024)
Presentation / Conference Contribution
Qiao, T., Li, R., Li, F. W. B., & Shum, H. P. H. (2024, December). From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos. Presented at ICPR 2024: International Conference on Pattern Recognition, Kolkata, India

Video-based Human-Object Interaction (HOI) recognition explores the intricate dynamics between humans and objects, which are essential for a comprehensive understanding of human behavior and intentions. While previous work has made significant stride... Read More about From Category to Scenery: An End-to-End Framework for Multi-Person Human-Object Interaction Recognition in Videos.

SK_DU Team: Cross-Encoder based Evidence Retrieval and Question Generation with Improved Prompt for the AVeriTeC Shared Task (2024)
Presentation / Conference Contribution
Malviya, S., & Katsigiannis, S. (2024, November). SK_DU Team: Cross-Encoder based Evidence Retrieval and Question Generation with Improved Prompt for the AVeriTeC Shared Task. Presented at 7th Fact Extraction and VERification Workshop (FEVER), Miami, Florida, USA

As part of the AVeriTeC shared task, we developed a pipelined system comprising robust and finely tuned models. Our system integrates advanced techniques for evidence retrieval and question generation, leveraging cross-encoders and large language mod... Read More about SK_DU Team: Cross-Encoder based Evidence Retrieval and Question Generation with Improved Prompt for the AVeriTeC Shared Task.

Evidence Retrieval for Fact Verification using Multi-stage Reranking (2024)
Presentation / Conference Contribution
Malviya, S., & Katsigiannis, S. (2024, November). Evidence Retrieval for Fact Verification using Multi-stage Reranking. Presented at 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), Miami, FL, USA

Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum (2024)
Presentation / Conference Contribution
Dua, A., Singh Aujla, G., Jindal, A., & Sun, H. (2024, December). Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum. Presented at IEEE Global Communications Conference - Workshop on Next-Gen Healthcare Fusion (NgHF): AI-driven Secure Integrated Networks for Healthcare IoT Systems, Cape Town, South Africa

The increasing demand for machine learning (ML) technologies has led to a significant rise in energy consumption and environmental impact, particularly within the context of distributed computing environments like the Edge-Fog-Cloud Continuum. This p... Read More about Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum.