Dr Lina Stankovic

Reader

Electronic and Electrical Engineering

Personal statement

My research expertise is in Signal and Information Processing, with focus on representation, processing, analysis, communications and data management of information in a range of signals including electrical signals, video, seismic/geoscience, health/biological and other environmental sensor data. Besides the Energy dimension of the work, the research insights gained are also applicable to appliance manufacturing and food systems, especially in relation to environmental impact assessment and net zero GHG emissions. Overall my research interests revolve around sustainability. My work is particularly aligned with the following university strategic research themes (Measurement Science & Enabling Technologies, Energy, Health & Well-Being)

I am also 1st year advisor of studies for the Computer and Electronic Systems degree at Strathclyde.

Expertise

Has expertise in:

Signal information processing with application to the following problems:

Non-intrusive load monitoring, load profiling and disaggregation, activity recognition in smart buildings (Energy and environment)
Motion capture and person-centric kinematrics analysis using portable depth and infrared camera systems (Health & Wellbeing)
Micro-seismic event analysis, inc. earthquakes (Geosciences)
Wireless sensor network solutions for civil infrastructure, such as predicting failure in earthworks (embankments and cuttings) and bridge/scour monitoring
Water consumption, treatment and infrastructure monitoring

Prizes 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

More prizes and awards

Qualifications

Senior Member of the IEEE

Publications

Individualised responsible Artificial Intelligence for home-based rehabilitation: Vourganas Ioannis, Stankovic Vladimir, Stankovic Lina; Sensors Vol 21 (2020); https://doi.org/10.3390/s21010002
Automatic detection and classification of microseismic events from Super-Sauze landslide using convolutional neural networks: Jiang Jiaxin, Stankovic Lina, Stankovic Vladimir, Pytharouli Stella; AGU Fall Meeting 2020 (2020)
Building a graph signal processing model using dynamic time warping for load disaggregation: He Kanghang, Stankovic Vladimir, Stankovic Lina; Sensors Vol 20 (2020); https://doi.org/10.3390/s20226628
Explainable NILM Networks: Murray David, Stankovic Lina, Stankovic Vladimir; 5th International Workshop on Non Intrusive Load Monitoring (2020)
Evaluation of low-complexity supervised and unsupervised NILM methods and pre-processing for detection of multistate white goods: Khazaei Mohammad, Stankovic Lina, Stankovic Vladimir; 5th International Workshop on Non Intrusive Load Monitoring (2020)
Robust deep graph based learning for binary classification: Ye Minxiang, Stankovic Vladimir, Stankovic Lina, Cheung Gene; IEEE Transactions on Signal and Information Processing over Networks (2020)

More publications

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

Research interests

Smart meter energy analytics, including load disaggregation, prediction and profiling
Non-intrusive Load Monitoring, residential and commercial
Environmental impact assessment of consumption cycle of Food Systems and Appliances
Detecting, classifying, understanding and characterising subsurface processes arising from man-made/induced activities, such as hydraulic fracturing
Model-fitting/system characterisation
Sensor deployment and data acquisition

Professional activities

External examiner for PhD defense of Tien Huu Do at Vrije Universiteit Brussel: Examiner; 2/12/2020
5th International Workshop on Non Intrusive Load Monitoring: Organiser; 18/11/2020
External examiner for PhD defense of Simon Henriet, Telecom Paris: Examiner; 16/9/2020
Appliance Usage Detection from Smart Meter Data Using Supervised and Unsupervised Non-Intrusive Load Monitoring: Contributor; 26/5/2020
External examiner for Megha Gaur, PhD Candidate, IIIT New Delhi, India: Examiner; 16/10/2019
PGCon: Edinburgh Postgraduate Conference: Participant; 15/10/2019

More professional activities

Projects

Smart pumping for Subsurface Engineering (Prosperity Partnership): Shipton, Zoe (Principal Investigator) Corney, Jonathan (Co-investigator) Dempster, William (Co-investigator) Perry, Marcus (Co-investigator) Pytharouli, Stella (Co-investigator) Stankovic, Lina (Co-investigator) Stankovic, Vladimir (Co-investigator) Yang, Shangtong (Co-investigator) Fan, Ding (Researcher) Parastatidis, Emmanouil (Researcher) Rizzuto, Francesco (Researcher) Xi, Xun (Researcher); 01-Jan-2018 - 31-Jan-2023
Eco-Bot: Personalised ICT-tools for the Active Engagement of Consumers Towards Sustainable Energy: Stankovic, Lina (Principal Investigator) Stankovic, Vladimir (Co-investigator) Murray, David (Researcher); 01-Jan-2017 - 31-Jan-2020
EPSRC Global Challenges Research Fund Institutional Sponsorship Award 2017 (GCRF) / R171051-102: Stankovic, Vladimir (Principal Investigator) Stankovic, Lina (Co-investigator); 01-Jan-2017 - 31-Jan-2018
SENSors and Intelligence in BuiLt Environment (SENSIBLE) MSCA RISE: Stankovic, Lina (Principal Investigator) Glesk, Ivan (Co-investigator) Gleskova, Helena (Co-investigator) Stankovic, Vladimir (Co-investigator); 01-Jan-2017 - 31-Jan-2020
Smart Building Energy Management System (BEMS): Stankovic, Lina (Principal Investigator); Market study and prototyping of data analytical tools that could be beneficial to utilities for improving their customer experience; 01-Jan-2013 - 30-Jan-2015
Monitoring ozone treatment technology: Stankovic, Lina (Principal Investigator) Andonovic, Ivan (Co-investigator) Stankovic, Vladimir (Co-investigator); 13-Jan-2013 - 31-Jan-2014

More projects

Address

Electronic and Electrical Engineering
Royal College Building

Location Map

View University of Strathclyde in a larger map