Ellen Zapata-Webborn

I am a Senior Research Fellow in Data Science and End Use Energy Demand at the UCL Energy Institute working on the Smart Energy Research Lab (SERL) project - developing a longitudinal smart meter dataset (with contextual data) for UK-based researchers.


  • Smart meter data
  • Machine learning
  • Power system operation and flexibility
  • Demand response
  • Energy consumption patterns
  • Fuel poverty


  • PhD in Mathematics and Complexity Science, 2018

    University of Warwick

  • MSc in Complexity Science, 2012

    University of Warwick

  • BSc in Mathematics with Intercalated Year, 2011

    University of Warwick

Recent Posts

Why nuclear power will (and won't) stop climate change

I was recently interviewed by science communicator Simon Clark for his latest science video “Why nuclear power will (and won’t) stop climate change” (below). The final result is a brilliant deep dive into nuclear power, and the nuclear versus renewables decarbonisation debate.

Bringing papers alive with video abstracts

As an early-career researcher, building up a decent publication record can feel like a real battle. By the time you’ve finished your work and written it up according to your chosen journal’s particular specifications, the last thing you might feel like doing is spending more time getting it publication-ready.

Recent Publications

Smart Energy Research Lab: Energy use in GB domestic buildings 2021

This report describes domestic gas and electricity energy use in Great Britain in 2021 based on data from the Smart Energy Research Lab (SERL) Observatory, which consists of smart meter and contextual …

Survey study on energy use in UK homes during Covid-19

To contain the spread of Covid-19, governments across the world imposed partial or complete lockdowns. National energy demand decreased in periods of lockdowns; however, as people spent more time at …

The SERL Observatory Dataset: Longitudinal Smart Meter Electricity and Gas Data, Survey, EPC and Climate Data for over 13,000 Households in Great Britain

The Smart Energy Research Lab (SERL) Observatory dataset described here comprises half-hourly and daily electricity and gas data, SERL survey data, Energy Performance Certificate (EPC) input data and …

Explaining daily energy demand in British housing using linked smart meter and socio-technical data in a bottom-up statistical model

This paper investigates factors associated with variation in daily total (electricity and gas) energy consumption in domestic buildings using linked pre-COVID-19 smart meter, weather, building thermal …

Increasing response rates and improving research design: Learnings from the Smart Energy Research Lab in the United Kingdom

Obtaining high-resolution energy consumption data from a large, representative sample of homes is critical for research, but low response rates, sample bias and high recruitment costs form substantial …