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Dr Phil Symonds
Lecturer in Machine Learning for Smart Buildings and Cities
Bartlett School Env, Energy & Resources
Faculty of the Built Environment
- Joined UCL
- 1st Nov 2014
Research summary
Phil is involved in a variety research projects related to the health impacts of decarbonising the built environment. His expertise lies in model development and the analysis of large datasets through the use of cutting edge statistical and machine learning methods with high performance computing.
Phil is the lead developer a microsimulation model in collaboration with researchers at the London School of Hygiene and Tropical Medicine which is used to assess the impacts of air pollution policy on cardiovascular morbidity.
He has also developed a metamodelling framework using artificial neural networks based on EnergyPlus simulations which has been used to look at how energy efficiency interventions in homes modify population exposure to overheating and air pollution. Results from EnergyPlus models have been compared to empirical data from the Energy Follow-Up Survey to assess their validity. Future work will seek to gain a better understanding of occupancy behaviour and the relationships humans have with the built environment.
Teaching summary
Phil is module leader of the Advanced Building Simulation module.
Education
- Brunel University
- Doctorate, Doctor of Philosophy | 2014
- University of Leeds
- Other higher degree, Master of Physics | 2010
Biography
Phil Symonds joined UCL IEDE in 2014 as a research associate. He is currently funded by the Wellcome Trust funded project 'Complex Urban Systems for Sustainability and Health' which seeks engage with stakeholders in several cities to identify healthy decarbonisation pathways. Phil’s research interests include computational modelling and the analysis of built environment data through the use of statistical techniques. Prior to joining UCL IEDE, Phil completed a PhD in Experimental Particle Physics at Brunel University (2010-2014). During his PhD, he was based at the Center for European Nuclear Research (CERN) for 18 months as a member of the Compact Muon Solenoid (CMS) experiment.