2023

Optimal scheduling of electric vehicle charging with deep reinforcement learning considering end users flexibility
C. Menos-Aikateriniadis, S. Sykiotis and P. S. Georgilakis, “Optimal scheduling of electric vehicle charging with deep reinforcement learning considering end users flexibility,” 13th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2022), Hybrid Conference, Valletta, Malta, 2022, pp. 284-289, doi: 10.1049/icp.2023.0007.
Continilm: A Continual Learning Scheme for Non-Intrusive Load Monitoring
S. Sykiotis, M. Kaselimi, A. Doulamis and N. Doulamis, “Continilm: A Continual Learning Scheme for Non-Intrusive Load Monitoring,” ICASSP 2023 – 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-5, doi: 10.1109/ICASSP49357.2023.10095696.
An active learning framework for the low-frequency Non-Intrusive Load Monitoring problem
Todic, T., Stankovic, V., & Stankovic, L. (2023). An active learning framework for the low-frequency Non-Intrusive Load Monitoring problem. Applied Energy, 341, 121078.
Review on the Application Areas of Decision-Making Algorithms in Smart Homes
Jin, L., & Boden, A. (2023). Review on the Application Areas of Decision-Making Algorithms in Smart Homes. In HHAI 2023: Augmenting Human Intellect (pp. 74-92). IOS Press
The design space of building user-centered AI user interfaces for smart heating systems.
Jin, L., & Boden, A. (2023). The design space of building user-centered AI user interfaces for smart heating systems. Mensch und Computer 2023. UCAI 2023: Workshop on User-Centered Artificial Intelligence. Rapperswil. 3.-6. September 2023
A self-sustained EV charging framework with N-step deep reinforcement learning
Sykiotis, S., Menos-Aikateriniadis, C., Doulamis, A., Doulamis, N., & Georgilakis, P. S. (2023). A self-sustained EV charging framework with N-step deep reinforcement learning. Sustainable Energy, Grids and Networks, 101124.
Towards transparent load disaggregation–a framework for quantitative evaluation of explainability using explainable AI
Batic, D., Stankovic, V., & Stankovic, L. (2023). Towards transparent load disaggregation–a framework for quantitative evaluation of explainability using explainable AI. IEEE Transactions on Consumer Electronics.
Social justice implications of smart urban technologies: an intersectional approach
Sharma, N. K., Hargreaves, T., & Pallett, H. (2023). Social justice implications of smart urban technologies: an intersectional approach. Buildings and Cities, 4(1), 315-333
Performance-aware NILM model optimization for edge deployment
Sykiotis, S., Athanasoulias, S., Kaselimi, M., Doulamis, A., Doulamis, N., Stankovic, L., & Stankovic, V. (2023). Performance-aware NILM model optimization for edge deployment. IEEE Transactions on Green Communications and Networking.
Improving knowledge distillation for non-intrusive load monitoring through explainability guided learning
Batic, D., Tanoni, G., Stankovic, L., Stankovic, V., & Principi, E. (2023). Improving knowledge distillation for non-intrusive load monitoring through explainability guided learning.

2022

[Dataset] Todic, T. (Creator), Stankovic, L. (Supervisor), Stankovic, V. (Supervisor) (28 Nov 2022). Electricity consumption measurements from three dairy farms in Germany. University of Strathclyde. ReadMe(.txt), location_20(.csv), location_18(.csv), location_21(.csv). 10.15129/cc3d1dcd-0ffb-4c38-aab7-b47712938d13
A First Approach using Graph Neural Networks on Non-Intrusive-Load-Monitoring
Athanasoulias, S., Sykiotis, S., Kaselimi, M., Protopapadakis, E., & Ipiotis, N. (2022, June). A First Approach using Graph Neural Networks on Non-Intrusive-Load-Monitoring. In Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 601-607).
Solar Power driven EV Charging Optimization with Deep Reinforcement Learning
Sykiotis, S., Menos-Aikateriniadis, C., Doulamis, A., Doulamis, N., & Georgilakis, P. S. (2022, October). Solar Power driven EV Charging Optimization with Deep Reinforcement Learning. In 2022 2nd International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED) (pp. 1-6). IEEE.
Electricity: An efficient transformer for non-intrusive load monitoring
Sykiotis, S., Kaselimi, M., Doulamis, A., & Doulamis, N. (2022). Electricity: An efficient transformer for non-intrusive load monitoring. Sensors, 22(8), 2926.
Visual prototyping the Smart-House future: a proposed co-design experience based on the collective imaginary from the cinema
Pereira, V., & Barros, G. (2022). Visual prototyping the Smart-House future: a proposed co-design experience based on the collective imaginary from the cinema. (In) Rautenberg, M,; Laffont, G. & Rozestraten, A. (Eds). Actes du IV Colloque International Imaginaire: Construire et Habiter la Terre: mégalopoles, métropoles, villes à la campagne, villes décroissantes. Quels imaginaires pour la ville de demain?. IV Colloque International Imaginaire: Construire et Habiter la Terre: mégalopoles, métropoles, villes à la campagne, villes décroissantes. Quels imaginaires pour la ville de demain?, Oct 2021, Saint-Étienne, France. 2021.
Towards user-centered explainable energy demand forecasting systems
Shajalal, M., Boden, A., & Stevens, G. (2022, June). Towards user-centered explainable energy demand forecasting systems. In Proceedings of the Thirteenth ACM International Conference on Future Energy Systems (pp. 446-447).
Automated Decision Making Systems in Smart Homes: A Study on User Engagement and Design
Jin, L., Boden, A., & Shajalal, M. (2022). Automated Decision Making Systems in Smart Homes: A Study on User Engagement and Design.
Quantification of dairy farm energy consumption to support the transition to sustainable farming
Todic, T., Stankovic, L., Stankovic, V., & Shi, J. (2022, June). Quantification of dairy farm energy consumption to support the transition to sustainable farming. In 2022 IEEE International Conference on Smart Computing (SMARTCOMP) (pp. 368-373). IEEE.
Particle swarm optimization in residential demand-side management: A review on scheduling and control algorithms for demand response provision
Menos-Aikateriniadis, C., Lamprinos, I., & Georgilakis, P. S. (2022). Particle swarm optimization in residential demand-side management: A review on scheduling and control algorithms for demand response provision. Energies, 15(6), 2211.
Low-frequency non-intrusive load monitoring of electric vehicles in houses with solar generation: generalisability and transferability
Vavouris, A., Garside, B., Stankovic, L., & Stankovic, V. (2022). Low-frequency non-intrusive load monitoring of electric vehicles in houses with solar generation: generalisability and transferability. Energies, 15(6), 2200.
An Efficient Deep Bidirectional Transformer Model for Energy Disaggregation
Sykiotis, S., Kaselimi, M., Doulamis, A., & Doulamis, N. (2022, August). An Efficient Deep Bidirectional Transformer Model for Energy Disaggregation. In 2022 30th European Signal Processing Conference (EUSIPCO) (pp. 1536-1540). IEEE.
Analysing co-design methods applied to energy-related smart home technologies
Guasselli, F. C., Gram-Hanssen, K., & Pereira, V. (2022, June). Analysing co-design methods applied to energy-related smart home technologies. In eceee Summer Study on Energy Efficiency: Agents of Change.
Social (In) Justice and the Smart Grid Transition: How do smart grid technologies aggravate injustices against marginalized groups?
Sharma, N. (2022). Social (In) Justice and the Smart Grid Transition: How do smart grid technologies aggravate injustices against marginalized groups?.
Focus on what matters: improved feature selection techniques for personal thermal comfort modelling
Shajalal, M., Bohlouli, M., Das, H. P., Boden, A., & Stevens, G. (2022, November). Focus on what matters: improved feature selection techniques for personal thermal comfort modelling. In Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 496-499).
Explainable product backorder prediction exploiting CNN: Introducing explainable models in businesses
Shajalal, M., Boden, A., & Stevens, G. (2022). Explainable product backorder prediction exploiting CNN: Introducing explainable models in businesses. Electronic Markets, 1-16.
Time Series Anomaly Detection in Smart Homes: A Deep Learning Approach
Zamani, S., Talebi, H., & Stevens, G. (2022). Time Series Anomaly Detection in Smart Homes: A Deep Learning Approach.
Smart meter electricity of a Household in Germany with Electric Vehicle Charging Annotation
Stankovic, L. (Supervisor), Stankovic, V. (Supervisor) (29 Aug 2022). Smart meter electricity of a Household in Germany with Electric Vehicle Charging Annotation. University of Strathclyde. ReadMe(.txt), discovergyTesla1min(.csv). 10.15129/c41a6a02-5df5-4ed7-b8e6-6488895d43f7
Appliance Phase Identification on ECO Dataset
Vavouris, A. (Creator), Stankovic, L. (Supervisor), Stankovic, V. (Supervisor) (6 Oct 2022). Appliance Phase Identification on ECO Dataset. University of Strathclyde. AppliancePhaseInformation(.csv), ReadMe(.txt). 10.15129/deddd9a7-0cff-4db2-8478-42abc93fba9f
Benefits of three-phase metering for load disaggregation
Vavouris, A., Stankovic, L., Stankovic, V., & Shi, J. (2022, November). Benefits of three-phase metering for load disaggregation. In Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 393-397).

2021

Collective construction of responsible and explainable AI for Smart Home technologies
Pereira, V. (2021). Collective construction of responsible and explainable AI for Smart Home technologies. Poster presentation at the ARIES Winter School, Norwich, UK. Nov 24-26, 2021.