Lindsay Lee

Background

About Lindsay Lee

I am a data scientist with a PhD in Probability and Statistics and a passion for advocating the use of statistics and machine learning for problem solving. My research interests are using advanced statistical methods to better understand complex systems and computer model responses and the visualisation of statistical results for real-world interpretation. I currently work on various projects where I have input in data capture and data storage, experimental design, exploratory data analysis, computer vision and neural networks. In all cases I work closely with domain experts to understand the problems to be solved using data, finding the most appropriate tools and accurate solutions. I have carried out a sensitivity analysis of the global aerosol model GLOMAP (developed at Leeds) in order to assess the effects of uncertainty in the model parameters on model predictions. In order to carry out the sensitivity analysis I conducted an expert elicitation, designed a set of model runs for emulation, and built and validated Gaussian Process emulators for univariate model outputs. The main challenge for me as a statistician was using these methods to provide information about a global model and producing visualisations and results that could be interpreted by the modellers.