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Laura Hattam

My research interests are in Applied Mathematics and modelling real-world systems. Past projects that I have been involved with include differential equation modelling, predictive data modelling, sequential Monte Carlo methods, agent-based modelling, machine learning bias mitigation methods, finite element modelling, recurrence quantification analysis, social network analysis, and signal processing. I have experience with working with large datasets, in particular, those related to electric power systems.

Before my current role, I was a Postdoc at the University of Reading, where I was part of the Thames Valley Vision Project with project partners Scottish and Southern Electricity Networks, which entailed forecasting the uptake of low carbon technologies due to social factors with agent-based modelling, as well as estimating the load impact on the UK electricity network. In addition, through this role, I worked with AND Technology Research developing an energy disaggregation algorithm that used a dynamical systems approach, which was implemented with their energy monitoring equipment.

Prior to this, I completed my PhD at Monash University, Australia, which focused on multi-scale asymptotic theory, entitled Modulation Theory for the Korteweg-de Vries Equation with Damping and Periodic Forcing. Also, prior to this, I obtained a BSc (Hons) in Applied Mathematics and Physics at the University of Melbourne, Australia.