Research output per year
Research output per year
DR
I currently work part-time as a Senior Researcher on three projects within the SUSTAIN Lab in the School of Informatics, University of Edinburgh.
Describing and Explaining Domestic Energy Use in Scotland (DEDEUS): This EPSRC-funded project, part of the wider Smart Energy Research Lab project, aims to provide a detailed understanding of patterns of gas and electricity use in Scottish households, and to investigate the household, building, behavioural and contextual factors which shape them, to provide insights for Scotland's energy transition. Read more about DEDEUS. Read more about SERL.
DISPATCH: In this EPSRC-funded project we, along with our project partners, are exploring energy demand for heating in domestic and small non-domestic buildings - current patterns of demand, and effective and equitable technology pathways for decarbonising buildings, recognising their diverse physical characteristics and occupant needs and requirements.
Smart Energy Savings (SENS): The Department of Business, Energy and Industrial Strategy (BEIS) has funded trials of several innovative energy feedback technologies drawing on smart meter data. I work as part of the independent 'Trial Design and Evaluation Lead' that has been developing the research designs and will undertake evaluations of the technologies' impacts on energy use and other outcomes. Read more about SENS.
For the remainder of my time, I work as a Senior Research Fellow in Data Science and End Use Energy at the UCL Energy Institute. View my UCL profile page.
IDEAL - Smarter home energy systems (2013-2019)
This large, EPSRC-funded project explored the potential of enhanced sensor systems and Machine Learning methods to improve energy feedback displays in homes. My work evaluated the impacts of these systems on occupant energy awareness and attitudes, as well as changes in energy using activities and actual energy use. Read more about IDEAL.
BIGSMALL - Measuring (un)sustainable practices (2015-2018)
This EPSRC-funded project developed novel machine learning methods for inferring household energy using practices based on the 'traces' they leave in signals from a variety of sensors in the home (electricity and gas use, temperature and humidity). The project helped determine the extent to which the performance of everyday energy using activities can be inferred based on smart meter data and other data sources. My work evaluated the potential for these inferences to a) help us better understand the relationships between energy-using activities, their impacts, and the factors which shape them; and b) provide enhanced feedback to householders.
Much of my earlier research focused on how changes in our domestic practices can enable us to lead less resource (energy and water) intensive, whilst possibly more fulfilling, lifestyles. I have a background in understanding how patterns of work (Pullinger, 2011, 2013) and everyday practices (Pullinger, Anderson, Browne, & Medd, 2013) influence carbon footprints, energy and water use in the home, as well as wellbeing, and how options for changing individual practices are shaped and constrained by wider policy and socio-technical systems (Pullinger 2011, 2013, 2014; Pullinger, Lovell and Webb, 2014; Browne, Medd, Pullinger, & Anderson, 2014). I have contributed to the development of new quantitative and mixed methods approaches to measuring and tracking practices, their influences and their impacts (Browne, Pullinger, Medd, & Anderson, 2014).
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Arvind, D. K. (Creator), Lovell, H. (Creator), Moore, J. (Creator), Shipworth, D. (Creator), Sutton, C. (Creator), Berliner, N. (Creator), Dzikovska, M. (Creator), Farrow, E. (Creator), Farrow, E. (Creator), Mann, J. (Creator), Morgan, E. (Creator), Webb, L. (Creator), Brewitt, C. (Creator), Zhong, M. (Creator), Webb, J. (Creator), Goddard, N. (Creator), Kilgour, J. (Creator) & Pullinger, M. (Creator), Edinburgh DataShare, 23 Apr 2021
DOI: 10.7488/ds/2836
Dataset
12/05/14
2 items of Media coverage
Press/Media: Research