My name is Oliver Parson, and I'm currently employed as a Senior Data Scientist at Bulb. I'm interested in investigating the ways in which machine learning can be used to break down household energy consumption data into individual appliances, also known as Non-intrusive Appliance Load Monitoring (NILM) or energy disaggregation.
Monday, 13 July 2015
NILM 2015 presentation videos
In case you missed the live stream of the Second European NILM Workshop, we've also uploaded each talk to a YouTube playlist.
Oliver Parson, University of Southampton - Introduction
Mario Bergés, CMU - NILM in the era of IoT
A series of 1-minute lightning talks by each poster presenter
Stephen Makonin, Simon Fraser University - From socioeconomic concerns to standardising accuracy to water NILM
Mingjun Zhong, University of Edinburgh - Incorporating long-term and population-level information into Machine-Learning based NILM
Imperial MSc Group - green gauge: Comparing Algorithms for Energy Disaggregation
Bruno Charbonnier, EDF - Decortic: A method for detecting and estimating the consumption of electrical space heating
Hjalmar Nilsonne - Connecting the world’s energy data
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