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A study on the impact of different components of a traditional webcam-based 2D gaze tracking algorithm (2025)
Journal Article
Blakey, W., Katsigiannis, S., & Ramzan, N. (online). A study on the impact of different components of a traditional webcam-based 2D gaze tracking algorithm. IEEE Sensors Journal, https://doi.org/10.1109/JSEN.2025.3564397

Webcam-based 2D gaze tracking algorithms are lightweight and are becoming increasingly used in the fields of medicine, market research and many others. As they become increasingly used, it becomes vital to break down their components to understand th... Read More about A study on the impact of different components of a traditional webcam-based 2D gaze tracking algorithm.

Too important to be left to the Generals: The Politics of the Western Front (2025)
Book Chapter
Johnson, M. (in press). Too important to be left to the Generals: The Politics of the Western Front. In The Cambridge Companion to the Western Front. Cambridge University Press

‘War is too important to be left to the generals.’ This aphorism, commonly attributed to the French Premier Georges Clemenceau, captures one of the most significant dilemmas to confront the states that went to war in the summer of 1914: should the pr... Read More about Too important to be left to the Generals: The Politics of the Western Front.

Coordination Mechanisms in AI Development: Practitioner Experiences on Integrating UX Activities (2025)
Presentation / Conference Contribution
Bruun, A., Van Berkel, N., Raptis, D., & Law, E. L.-C. (2025, April). Coordination Mechanisms in AI Development: Practitioner Experiences on Integrating UX Activities. Presented at CHI 2025 (Conference on Human Factors in Computing Systems), Yokohama, Japan

Software development relies on collaboration and alignment between a variety of roles, including software developers and user experience designers. The increasing focus on artificial intelligence in today's development projects has given rise to new... Read More about Coordination Mechanisms in AI Development: Practitioner Experiences on Integrating UX Activities.

Deep Reinforcement Learning for Overtaking Decision-Making and Planning of Autonomous Vehicles (2025)
Presentation / Conference Contribution
Aihaiti, A., Arvin, F., & Hu, J. (2025, March). Deep Reinforcement Learning for Overtaking Decision-Making and Planning of Autonomous Vehicles. Presented at 2025 IEEE International Conference on Industrial Technology, Wuhan, China

The safe overtaking of autonomous vehicles has become an important focus in recent robotics and AI research. Considering the scenario of overtaking with oncoming vehicles, this paper proposes a hierarchical framework based on deep reinforcement learn... Read More about Deep Reinforcement Learning for Overtaking Decision-Making and Planning of Autonomous Vehicles.

T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles (2025)
Journal Article
Pan, H., Zahmatkesh, M., Rekabi-Bana, F., Arvin, F., & Hu, J. (online). T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles. IEEE Transactions on Intelligent Transportation Systems, https://doi.org/10.1109/TITS.2025.3557783

This paper introduces a time-optimal swarm tra-jectory planner for cooperative unmanned aerial vehicle (UAV) systems, designed to generate collision-free trajectories for flocking control in cluttered environments. To achieve this goal, model predict... Read More about T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles.

Human Intracranial EEG Biometric Identification (2025)
Presentation / Conference Contribution
Belay, B., & Katsigiannis, S. (2025, July). Human Intracranial EEG Biometric Identification. Presented at International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC), Copenhagen, Denmark

SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM (2025)
Presentation / Conference Contribution
Chen, S., Zhang, H., Atapour-Abarghouei, A., & Shum, H. P. H. (2025, February). SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM. Presented at 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Tucson, Arizona

Image inpainting aims to repair a partially damaged image based on the information from known regions of the images. Achieving semantically plausible inpainting results is particularly challenging because it requires the reconstructed regions to exhi... Read More about SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM.

Towards empathic medical conversation in Narrative Medicine: A visualization approach based on intelligence augmentation (2025)
Journal Article
Ma, H., Law, E. L.-C., Sun, X., Yang, W., He, X., Lawson, G., Zheng, H., Wang, Q., Li, Q., & Yuan, X. (2025). Towards empathic medical conversation in Narrative Medicine: A visualization approach based on intelligence augmentation. International Journal of Human-Computer Studies, 199, Article 103506. https://doi.org/10.1016/j.ijhcs.2025.103506

Empathic medical conversation is central to patient-centered care within Narrative Medicine. However, difficulties, such as physicians’ limited empathic capabilities and lack of time, impede the practice. Research on real-time, on-site empathic medic... Read More about Towards empathic medical conversation in Narrative Medicine: A visualization approach based on intelligence augmentation.

Model‐Driven Engineering for Digital Twins: Opportunities and Challenges (2025)
Journal Article
Michael, J., Cleophas, L., Zschaler, S., Clark, T., Combemale, B., Godfrey, T., Khelladi, D. E., Kulkarni, V., Lehner, D., Rumpe, B., Wimmer, M., Wortmann, A., Ali, S., Barn, B., Barosan, I., Bencomo, N., Bordeleau, F., Grossmann, G., Karsai, G., Kopp, O., …Vangheluwe, H. (online). Model‐Driven Engineering for Digital Twins: Opportunities and Challenges. Systems Engineering, https://doi.org/10.1002/sys.21815

Digital twins are increasingly used across a wide range of industries. Modeling is a key to digital twin development—both when considering the models which a digital twin maintains of its real‐world complement (“models in digital twin”) and when cons... Read More about Model‐Driven Engineering for Digital Twins: Opportunities and Challenges.

Compiler support for semi-manual AoS-to-SoA conversions with data views (2025)
Presentation / Conference Contribution
Radtke, P., & Weinzierl, T. (2024, September). Compiler support for semi-manual AoS-to-SoA conversions with data views. Presented at PPAM 2024 - 15th International Conference on Parallel Processing & Applied Mathematics, Ostrava, Czech Republic

The C programming language and its cousins such as C++ stipulate the static storage of sets of structured data: Developers have to commit to one, invariant data model -- typically a structure-of-arrays (SoA) or an array-of-structs (AoS) -- unles... Read More about Compiler support for semi-manual AoS-to-SoA conversions with data views.

Semi-supervised Object-Wise Anomaly Detection for Firearm and Firearm Component Detection in X-ray Security Imagery (2025)
Presentation / Conference Contribution
Gaus, Y. F. A., Isaac-Medina, B. K. S., Bhowmik, N., Lam, Y. T., & Breckon, T. P. (2025, June). Semi-supervised Object-Wise Anomaly Detection for Firearm and Firearm Component Detection in X-ray Security Imagery. Presented at 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Nashville, Tennessee, USA

FineCausal: A Causal-Based Framework for Interpretable Fine-Grained Action Quality Assessment (2025)
Presentation / Conference Contribution
Han, R., Zhou, K., Atapour-Abarghouei, A., Liang, X., & Shum, H. P. H. (2025, June). FineCausal: A Causal-Based Framework for Interpretable Fine-Grained Action Quality Assessment. Presented at Proceedings of the 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025, Music City Center, Nashville TN

Action quality assessment (AQA) is critical for evaluating athletic performance, informing training strategies, and ensuring safety in competitive sports. However, existing deep learning approaches often operate as black boxes and are vulnerable to s... Read More about FineCausal: A Causal-Based Framework for Interpretable Fine-Grained Action Quality Assessment.

BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction (2025)
Journal Article
Li, R., Katsigiannis, S., Kim, T.-K., & Shum, H. P. H. (online). BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction. IEEE Transactions on Neural Networks and Learning Systems, https://doi.org/10.1109/TNNLS.2025.3545268

Trajectory prediction allows better decision-making in applications of autonomous vehicles (AVs) or surveillance by predicting the short-term future movement of traffic agents. It is classified into pedestrian or heterogeneous trajectory prediction.... Read More about BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction.

Reconfigurable routing in data center networks (2025)
Journal Article
Stewart, I., & Kutner, D. (2025). Reconfigurable routing in data center networks. Theoretical Computer Science, 1038, Article 115154. https://doi.org/10.1016/j.tcs.2025.115154

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.

Multi-modal Dynamic Point Cloud Geometric Compression Based on Bidirectional Recurrent Scene Flow* (2025)
Presentation / Conference Contribution
Nan, F., Li, F., Wang, Z., Tam, G. K. L., Jiang, Z., DongZheng, D., & Yang, B. (2025, April). Multi-modal Dynamic Point Cloud Geometric Compression Based on Bidirectional Recurrent Scene Flow*. Presented at ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India

Deep learning methods have recently shown significant promise in compressing the geometric features of point clouds. However, challenges arise when consecutive point clouds contain holes, resulting in incomplete information that complicates motion es... Read More about Multi-modal Dynamic Point Cloud Geometric Compression Based on Bidirectional Recurrent Scene Flow*.

Synergistic Reinforcement Learning Models for Pedestrian-Friendly Traffic Signal Control (2025)
Presentation / Conference Contribution
Chen, D., Hu, J., Zhang, H., & Chen, B. (2025, June). Synergistic Reinforcement Learning Models for Pedestrian-Friendly Traffic Signal Control. Presented at 2025 European Control Conference (ECC), Thessaloniki, Greece

Traffic signal control is essential for managing urban traffic, reducing congestion, and minimizing environmental impact by optimizing both vehicular and pedestrian flow. This paper investigates the application of Reinforcement Learning (RL) in traff... Read More about Synergistic Reinforcement Learning Models for Pedestrian-Friendly Traffic Signal Control.