Matthew Li

PhD MRes MMath

  • Research Associate in Operational Rating of Homes

Research and expertise

My interests and expertise include:

  • Data-driven methods for assessing in-use building energy efficiency and fabric thermal performance
  • Data-driven and statistical methods for characterizing and forecasting domestic energy demands
  • Identification and characterization of domestic overheating

Current research activity

  • Domestic Operational Rating (DOR): Development, Programming and Testing, EPSRC
  • Summertime overheating in English homes: a credible night-time overheating criterion

Recently completed research projects 

  • Thermal performance of UK dwellings: Assessment of methods for quantifying whole-dwelling heat loss in occupied homes, EPSRC (PhD research project)
  • Digital Energy Feedback and Control Technology Optimisation (DEFACTO), EPSRC (Research assistant data curator)

Recent publications

  • K.J. Lomas, D. Allinson, S. Watson, A. Beizaee, V.J. Haines, M. Li, Energy savings from domestic zonal heating controls: Robust evidence from a controlled field trial, Energy and Buildings (2022) 254, 111572. ISSN 0378-7788. DOI: 10.1016/j.enbuild.2021.111572.
  • M. Li, D. Allinson, K. Lomas, Estimation of building heat transfer coefficients from in-use data: Impacts of unmonitored energy flows, International Journal of Building Pathology and Adaptation (2019), Vol. 38 No. 1, pp. 38-50. ISSN: 2398-4708. DOI: 10.1108/IJBPA-02-2019-0022
  • M. Li, D. Allinson, M. He, Seasonal variation in household electricity demand: A comparison of monitored and synthetic daily load profiles, Energy and Buildings (2018) 179, 292-300. DOI: 10.1016/j.enbuild.2018.09.018


I contribute to the following learning and teaching activities:


  • Thermodynamics and heat transfer (Module assistant)


  • MRes Energy Demand Studies (Module assistant)
  • MRes and PhD projects (Supervisory contributions)


I joined Loughborough University in 2016 as a member of the London-Loughborough (LoLo) Centre for Doctoral Training in Energy Demand Studies. During an initial MRes year, I conducted a novel analysis of seasonality in monitored daily domestic electricity demand profiles, and their representation in load-modelling exercises.

My subsequent PhD project explored the applicability of methods for estimating the thermal performance of occupied dwellings using on-board monitoring data, and the means by which such methods may be evaluated.

I previously completed a Master of Mathematics degree at Oxford University, following which I spent five years teaching mathematics and statistics at Seoul Global High School, South Korea.

Key collaborators

My research and enterprise activities are conducted with a range of academic and stakeholder partners, including:

  • SmartEnergy Research Lab (SERL)
  • Arup
  • Department for Business, Energy and Industrial Strategy (BEIS)
  • Ministry of Housing, Communities & Local Government (MHCLG)