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Lina Stankovic

Dr

 https://orcid.org/0000-0002-8112-1976

  • United Kingdom

Accepting PhD Students

PhD projects

1. Explainable and Ethical AI for trust 2. Understanding energy demand and energy-intensive activities through data-driven AI methods 3. Non-Intrusive Appliance Load Monitoring (NILM) 4. Understanding subsurface processes for mitigating landslides or extracting geothermal energy through AI-driven micro-seismic signal analysis 5. Understanding the value of pipeline and end-to-end learning methods for different applications and datasets 5. AI methods for non-intrusive rehabilitation and telehealthcare

20012020

Research output per year

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Personal profile

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 & Capabilities

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

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

Academic / Professional qualifications

  • Senior Member of the IEEE

Teaching Interests

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

Education/Academic qualification

Doctor of Philosophy, School of Computing and Communications, Lancaster University

Award Date: 1 May 2003

Bachelor of Engineering, Lancaster University

Award Date: 15 Jun 1999

External positions

Committe member of the European Science Foundation, The European Science Foundation

Dec 2018 → Dec 2021

Editorial Board, Editorial Board of the IEEE Transactions on Signal and Information Processing over Networks

12 Feb 2018 → …

Carnegie Trust Research Assessor for Science, Engineering and Technology, Carnegie Trust for the Universities of Scotland

Feb 2018 → …

EPSRC Peer Review College Member , Engineering and Physical Sciences Research Council

1 Apr 2010 → …

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