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.
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Area of Expertise
Signal information processing with application to the following problems:
- Non-intrusive load monitoring (NILM), load profiling and disaggregation, activity recognition and anomaly detection from smart meter data (Energy)
- Downstream benefits of NILM for the built environment, agriculture and transport inc. EV (Innovation and Industry)
- Landslide mitigation and informing geothermal extraction through micro-seismic event analysis (Geosciences)
- Motion capture and person-centric kinematrics analysis using portable depth and infrared camera systems (Health & Wellbeing)
Prize And Awards
- 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
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Publications
- Geodemographic aware electric vehicle charging location planning for equitable placement using graph neural networks : case study of Scotland metropolitan areas
- Batic Djordje, Stankovic Vladimir, Stankovic Lina
- Energy Vol 324 (2025)
- https://doi.org/10.1016/j.energy.2025.135834
- A human-on-the-loop approach for labelling seismic recordings from landslide site via a multi-class deep-learning based classification model
- Jiang Jiaxin, Murray David, Stankovic Vladimir, Stankovic Lina, Hibert Clement, Pytharouli Stella, Malet Jean-Philippe
- Science of Remote Sensing Vol 11 (2025)
- https://doi.org/10.1016/j.srs.2024.100189
- Semi-supervised graph-based non-intrusive load monitoring method combining transformer and graph Laplacian smoothing
- Dong Jun, Zheng Jinming, Stankovic Lina, Stankovic Vladimir
- 2024 IEEE 8th Conference on Energy Internet and Energy System Integration (EI2) 8th IEEE Conference on Energy Internet and Energy System Integration, pp. 209-213 (2025)
- https://doi.org/10.1109/EI264398.2024.10991553
- A temporal-spatial graph network with a learnable adjacency matrix for appliance-level electricity consumption prediction
- Li Dandan, Xia Jiaxing, Li Jiangfeng, Xiao Changjiang, Stankovic Vladimir, Stankovic Lina, Shi Quingjiang
- IEEE Transactions on Artificial Intelligence Vol 6, pp. 989-1002 (2025)
- https://doi.org/10.1109/TAI.2024.3507734
- A weakly supervised active learning framework for non-intrusive load monitoring
- Tanoni Giulia, Sobot Tamara, Principi Emanuele, Stankovic Vladimir, Stankovic Lina, Squartini Stefano
- Integrated Computer-Aided Engineering Vol 32, pp. 39-56 (2025)
- https://doi.org/10.3233/ICA-240738
- XNILMBoost : explainability-informed load disaggregation training enhancement using attribution priors
- Batic Djordje, Stankovic Vladimir, Stankovic Lina
- Engineering Applications of Artificial Intelligence Vol 141 (2025)
- https://doi.org/10.1016/j.engappai.2024.109766
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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
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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
- 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
- 2025 Teaching Away Day
- Speaker
- 11/6/2025
- EPSRC Scoping Worskhop (Critical mass)
- Participant
- 30/1/2025
- Inter-disciplinary co-creation in JED-AI project
- Speaker
- 14/11/2024
- IEEE UK and Ireland Women in ComSoc Event
- Participant
- 4/11/2024
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
- 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
- JED-AIs: Justice, Energy, Demand flexibility and AI for Sustainability (UKRI Cross Research Council Resp Mode)
- Stankovic, Vladimir (Principal Investigator) Stankovic, Lina (Co-investigator)
- 26-Jan-2024 - 25-Jan-2026
- 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
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Contact
Professor
Lina
Stankovic
Electronic and Electrical Engineering
Email: lina.stankovic@strath.ac.uk
Tel: 548 2704