• United Kingdom

Accepting PhD Students

PhD projects

Understanding electrical energy demand through non-intrusive appliance load monitoring Understanding energy demand through activity recognition via heterogeneous sensor data Understanding subsurface processes through micro-seismic signal analysis Motion capture using depth and infrared sensor data Graph-based signal processing


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

Bachelor of Engineering, Lancaster University

External positions

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

Dec 2018Dec 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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Research Output

Deep-based conditional probability density function forecasting of residential loads

Afrasiabi, M., Mohammadi, M., Rastegar, M., Stankovic, L., Afrasiabi, S. & Khazaei, M., 31 Jul 2020, In : IEEE Transactions on Smart Grid. 11, 4, p. 3746-3757 12 p., 8988175.

Research output: Contribution to journalArticle

Open Access
  • 11 Downloads (Pure)

    Graph-based micro-seismic signal classification with an optimised feature space

    Li, J., Yang, C., Stankovic, V., Stankovic, L. & Pytharouli, S., 24 Jul 2020. 4 p.

    Research output: Contribution to conferencePaper

    Open Access
  • Thesis

    Enhancing livestock and human health monitoring via analysis of electronic sensor data

    Author: Sarkar, S., 20 May 2018

    Supervisor: Stankovic, L. (Supervisor) & Andonovic, I. (Supervisor)

    Student thesis: Doctoral Thesis

    Fast blind adaptive equalisation for multiuser CDMA systems

    Author: Daas, A., 19 Aug 2018

    Supervisor: Weiss, S. (Supervisor) & Stankovic, L. (Supervisor)

    Student thesis: Doctoral Thesis


    Finalist of the World first 10K Best paper Award (Top 3%)

    Minxiang Ye (Recipient), Cheng Yang (Recipient), Vladimir Stankovic (Recipient), Lina Stankovic (Recipient) & Samuel Cheng (Recipient), 12 Jul 2017

    Prize: Prize (including medals and awards)

  • Activities

    Appliance Usage Detection from Smart Meter Data Using Supervised and Unsupervised Non-Intrusive Load Monitoring

    Mohammad Khazaei (Speaker), Lina Stankovic (Contributor), Vladimir Stankovic (Contributor)
    26 May 202028 May 2020

    Activity: Talk or presentation typesOral presentation

    External examiner for Megha Gaur, PhD Candidate, IIIT New Delhi, India

    Lina Stankovic (Examiner)
    16 Oct 2019

    Activity: Examination typesExamination