Professor Lina Stankovic
Electronic and Electrical Engineering
Personal statement
Personal statement
My research expertise is in Signal and Information Processing (inc. AI technologies and machine learning), with focus on representation, processing, temporal and spatial information mining, and data management for a range of signal types acquired from sensors. My key strength is in extracting meaningful information from real data, including electrical, seismic, health/biological and other environmental sensor data, developing algorithms to handle dynamic and complex data that is often sparse, noisy, heterogeneous and multimodal, gathered from distributed sources. My research is multi-disciplinary by nature and has a strong focus on tackling emerging challenges pertaining to climate change and United Nations Sustainable Development Goals, working closely with international collaborators and non-academic stakeholders to lead innovation in the field.
My work is particularly aligned with the following university strategic research themes (Measurement Science & Enabling Technologies, Energy, Health & Well-Being)
I am currently Deputy Head of Department Learning & Teaching.
Back to staff profile
Prize And Awards
- Strategic Themes Research and Knowledge Exchange Impact Prize: Centre for Intelligent Dynamic Communications (CIDCOM) Team
- Recipient
- 25/8/2025
- Dumfries and Galloway Chamber of Commerce Net Zero Award
- Recipient
- 6/6/2025
- Finalist of the World first 10K Best paper Award (Top 3%)
- Recipient
- 12/7/2017
- Paper awarded top 5% by reviewers in Eusipco-2010 conference and invited for journal publication.
- Recipient
- 8/2010
Qualifications
PhD and BEng (Hons) in Electronic Communication Systems from Lancaster University
Back to staff profile
Publications
- ChargeDEM : geodemographic aware EV charging infrastructure placement for enhanced site selection using graph neural networks
- Batic Djordje, Stankovic Vladimir, Stankovic Lina
- Proceedings of the 12th International Conference on Energy Efficiency in Domestic Appliances and Lighting 12th International Conference on Energy Efficiency in Domestic Appliances and Lighting (EEDAL’24) Springer Proceedings in Energy (2026)
- Uncovering hidden demand flexibility using non-intrusive load monitoring (NILM) : a case for Southern Africa – Namibia
- Mollel Rachel Stephen, Elombo Andreas, Stankovic Lina, Stankovic Vladimir, Hambata Jona, Thiel Gunther
- Proceedings of the 12th International Conference on Energy Efficiency in Domestic Appliances and Lighting 12th International Conference on Energy Efficiency in Domestic Appliances and Lighting (EEDAL’24) Springer Proceedings in Energy (2026)
- Enhancement of hydrological time series prediction with Real-World Time Series Generative Adversarial Network-based synthetic data and deep learning models
- Dodig Ana, Stankovic Vladimir, Stankovic Lina, Stojkovic Milan
- Environmental Modelling and Software Vol 204 (2026)
- https://doi.org/10.1016/j.envsoft.2026.107037
- Physics-guided GRU model for stable multi-horizon displacement forecasting
- Parasyris Apostolos, Stankovic Lina, Stankovic Vladimir
- IEEE 7th International Conference in Electronic Engineering & Information Technology 2026 (2026)
- Reimagining emotion AI at home : exploring the potential of emotion-adaptive eco-feedback in personal assistant using matchmaking for AI
- Jin Lu, Vavouris Apostolos, Castelli Nico, Pins Dominik, Boden Alexander, Stankovic Lina, Stankovic Vladimir
- Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Vol 10 (2026)
- https://doi.org/10.1145/3789680
- Generative self-supervised learning for seismic event classification
- Jiang Jiaxin, Stankovic Vladimir, Stankovic Lina, Murray David, Pytharouli Stella
- Engineering Applications of Artificial Intelligence Vol 165 (2026)
- https://doi.org/10.1016/j.engappai.2025.113355
Back to staff profile
Teaching
Current classes:
1st year Engineering Design for Software Development inc. Python programming
4th/5th year Information Transmission and Security, inc. Digital communications principles, channel coding
Back to staff profile
Research Interests
- Smart meter energy analytics, including load disaggregation, prediction and profiling
- AI for the Decarbonisation of the Built Environment, Agriculture and Transport
- Environmental impact assessment of consumption cycle of Food Systems and Appliances inc. Electric Vehicles
- Detecting, classifying, understanding and characterising subsurface processes arising from natural slopes for landslide mitigation and human activities, such as geothermal extraction
- Model-fitting/system characterisation
- Sensor deployment and data acquisition
Professional Activities
- Learning from Multiple Data Modalities: Novel Model Architectures, Algorithms, and Applications to Healthcare Challenges
- Examiner
- 10/12/2025
- Towards Real-World NILM: Analytical and Empirical Procedures for Assessing Comparability and Reproducibility
- Examiner
- 26/11/2025
- Quantifying temporal and spatial causalities between climate change and slope failures through the use of Advanced AI
- Speaker
- 11/9/2025
- Automated Exploration and Analysis of Seismological Data Streams with Advanced AI-based technologies
- Examiner
- 11/9/2025
- International Joint Conference on Neural Networks 2025
- Organiser
- 30/6/2025
- Empowering tenants, Enhancing Lives: Housing associations and the future of energy advice
- Invited speaker
- 26/6/2025
Projects
- Digital Dairy Chain Innovation Voucher: An AI data-driven reporting dashboard for the dairy sector
- Stankovic, Lina (Principal Investigator) Stankovic, Vladimir (Co-investigator) Vavouris, Apostolos (Researcher)
- This project will develop a cost-effective (by leveraging on bespoke open-source agri software) AI-powered energy analytics dashboard designed for dairy farms, integrating real-time and historical energy data to provide automated insights into consumption, renewable generation, and cost/carbon-savings opportunities. By leveraging machine learning, the system will identify inefficiencies, predict energy demand, and recommend optimisation strategies to reduce costs and carbon footprint. The dashboard will process data from smart meters, IoT devices, and renewables, offering actionable insights through a user-friendly interface. Farm owners will receive data-driven recommendations to maximise renewable energy use, optimise time of use, and enhance overall efficiency. Further to that, the dashboard will support recommendations for installing energy saving technologies, altering processes or equipment to save energy and reduce their carbon impact. This innovative solution aims to streamline energy management in dairy farming, supporting sustainability and financial savings through AI-driven decision-making.
- 01-Jan-2025 - 30-Jan-2025
- JED-AIs: Justice, Energy, Demand flexibility and AI for Sustainability (UKRI Cross Research Council Resp Mode)
- Stankovic, Vladimir (Principal Investigator) Stankovic, Lina (Co-investigator)
- 01-Jan-2025 - 31-Jan-2026
- Picture-IT Create: Generative AI to support Diverse Learning Environments
- Stankovic, Lina (Principal Investigator) Stankovic, Vladimir (Co-investigator) Batic, Dorde (Researcher)
- 01-Jan-2024 - 31-Jan-2025
- REMINDA: Revolutionising Energy Monitoring in Non-Domestic Buildings with A.I
- Stankovic, Vladimir (Principal Investigator) Stankovic, Lina (Co-investigator)
- 01-Jan-2024 - 31-Jan-2025
- Digital Dairy Chain Innovation Voucher: Project Drum - How End Farm, community led RES surplus energy export potential and methane/gas production for self-consumption/export
- Stankovic, Lina (Principal Investigator) Stankovic, Vladimir (Co-investigator) Vavouris, Apostolos (Researcher)
- The goal of this project is to perform an analysis on the renewable energy exporting potential (wind/solar/anaerobic digester) in order to inform business case models that will explore community energy sharing schemes, battery storage and export, EV charging etc.
- 27-Jan-2024 - 31-Jan-2024
- Digital Dairy Chain Innovation Voucher: Project Drum - Beckside farm energy balancing and surplus exporting potential under a community led scheme
- Stankovic, Vladimir (Principal Investigator) Stankovic, Lina (Co-investigator) Vavouris, Apostolos (Researcher)
- In this project the optimal exploitation of the renewable energy surplus (solar/hydro) in dairy farms will be explored together with possibilities for load shifting in order to optimise the energy self-consumption. The exploitation of the available land and roof space for the installation of additional renewables to further increase the passive cash flows of the farm will also be explored, as well as investments in energy storage and diversifying clean energy production to inform further studies on community energy sharing and business models development for energy sharing.
- 27-Jan-2024 - 31-Jan-2024
Back to staff profile
Contact
Professor
Lina
Stankovic
Electronic and Electrical Engineering
Email: lina.stankovic@strath.ac.uk
Tel: 548 2704