Dynamic Calibration of Trust and Trustworthiness in AI-Enabled Systems (2025)
Journal Article
Liebherr, M., Enkel, E., Law, E. L.-C., Mousavi, M. R., Sammartino, M., & Sieberg, P. (in press). Dynamic Calibration of Trust and Trustworthiness in AI-Enabled Systems. International Journal on Software Tools for Technology Transfer,

Trust is a multi-faceted phenomenon traditionally studied in human relations and more recently in human-machine interactions. In the context of AI-enabled systems, trust is about the belief of the user that in a given scenario the system is going to... Read More about Dynamic Calibration of Trust and Trustworthiness in AI-Enabled Systems.

SKDU at De-Factify 4.0: Natural language features for AI-Generated Text-Detection (2025)
Presentation / Conference Contribution
Maviya, S., Arnau-González, P., Arevalillo-Herráez, M., & Katsigiannis, S. (2025, February). SKDU at De-Factify 4.0: Natural language features for AI-Generated Text-Detection. Presented at De-factify 4.0 Workshop at 39th Annual AAAI Conference on Artificial Intelligence, Philadelphia, PA, USA

SKDU at De-Factify 4.0: Vision Transformer with Data Augmentation for AI-Generated Image Detection (2025)
Presentation / Conference Contribution
Malviya, S., Bhowmik, N., & Katsigiannis, S. (2025, February). SKDU at De-Factify 4.0: Vision Transformer with Data Augmentation for AI-Generated Image Detection. Presented at De-factify 4.0 Workshop at the 39th Annual AAAI Conference on Artificial Intelligence, Philadelphia, PA, USA

T-BLAST: Token-Based Leveraging of Autonomous Spectrum Trading (2025)
Presentation / Conference Contribution
Singh, M., Bjorndahl, W., Aujla, G., & Camp, J. (2025, May). T-BLAST: Token-Based Leveraging of Autonomous Spectrum Trading. Presented at IEEE International Symposium on Dynamic Spectrum Access Networks, London

On the Locality of the Lovász Local Lemma (2025)
Presentation / Conference Contribution
Davies-Peck, P. (2025, June). On the Locality of the Lovász Local Lemma. Presented at 57th Annual ACM Symposium on Theory of Computing (STOC '25), Prague

The Lovász Local Lemma is a versatile result in probability theory, characterizing circumstances in which a collection of n ‘bad events’, each occurring with probability at most p and dependent on a set
of underlying random variables, can be avoided... Read More about On the Locality of the Lovász Local Lemma.

Deep Learning-Enhanced Visual Monitoring in Hazardous Underwater Environments with a Swarm of Micro-Robots (2025)
Presentation / Conference Contribution
Chen, S., He, Y., Lennox, B., Arvin, F., & Atapour-Abarghouei, A. (2025, May). Deep Learning-Enhanced Visual Monitoring in Hazardous Underwater Environments with a Swarm of Micro-Robots. Presented at IEEE International Conference on Robotics & Automation, Atlanta, USA

Long-term monitoring and exploration of extreme environments, such as underwater storage facilities, is costly, labor-intensive, and hazardous. Automating this process with low-cost, collaborative robots can greatly improve efficiency. These robots c... Read More about Deep Learning-Enhanced Visual Monitoring in Hazardous Underwater Environments with a Swarm of Micro-Robots.

Uncertainty-aware Probabilistic 3D Human Motion Forecasting via Invertible Networks (2025)
Presentation / Conference Contribution
Ma, Y., Zhou, K., Yu, F., Li, F. W. B., & Liang, X. (2025, May). Uncertainty-aware Probabilistic 3D Human Motion Forecasting via Invertible Networks. Paper presented at IEEE International Conference on Robotics and Automation 2025, Atlanta, USA

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.

Surprise! Surprise! Learn and Adapt (2024)
Presentation / Conference Contribution
Samin, H., Walton, D., & Bencomo, N. (2025, May). Surprise! Surprise! Learn and Adapt. Presented at 24th International Conference on Autonomous Agents and Multiagent Systems, Detroit, Michigan, USA

Self-adaptive systems (SAS) adjust their behavior at runtime in response to environmental changes, which are often unpredictable at design time. SAS must make decisions under uncertainty, balancing trade-offs between quality attributes (e.g., cost mi... Read More about Surprise! Surprise! Learn and Adapt.

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?.

Optimal Scheduling in a Quantum Switch (2024)
Journal Article
Bhambay, S., Vasantam, T., & Walton, N. (in press). Optimal Scheduling in a Quantum Switch. ACM SIGMETRICS Performance Evaluation Review,

With a growing number of quantum networks in operation, there is a pressing need for performance analysis of quantum switching technologies. A quantum switch establishes, distributes, and maintains entanglements across a network. In contrast to a cla... Read More about Optimal Scheduling in a Quantum Switch.

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.