My research project is on “Machine Learning for Wind Flow Modelling”, and aims to create machine learning models to predict the wind flow over a given area of terrain, which is a key part of wind energy resource assessments. There are a number of physics-based flow models already available, ranging from fast linear flow models to the more accurate, but more computationally expensive, CFD methods. Machine learning offers the potential to create models with the accuracy of CFD, but the speed of the simpler, linear flow models. This project is co-supervised between the University of Bristol and DNV, and hence has strong links to industry.

Before starting this research project, I worked for four years in the energy industry as a mechanical/software engineer, and I am particularly interested in applying cutting-edge research to solve real-world engineering problems.