Academic Biography
I am a Doctoral Scholar funded by the NERC UKRI Environmental Research Scholarship. I have a First Class BEng Engineering Degree, the Institute of Civil Engineers Award (2020) and a Master's of Science degree from the University of Oxford with distinction in my thesis and science examinations (2021). I will be entering the fourth year of a four year DPhil/PhD course in Physics this autumn, and am co-supervised across the Department of Physics (Professor Hannah Christensen) the School of Geography and the Environment (Professor Louise Slater), and ETH Zurich (Professor Manuela Brunner).
My research explores machine learning techniques to understand the physical processes and prediction pathways of hydro-climate extremes in the UK, mainly floods. I have worked on a project testing atmospheric circulation patterns association with flood events, and am currently working on a methodological comparison of machine learning (ML) models for the analysis of flood processes. I am also involved in collaborations with UKCEH and Hydro-Jules, for a UK Model Inter-comparison Project, and the influence of modes of climate variability on global natural flows using the ROBIN dataset.
I am an advanced coder in Python, and experienced using ML packages like scikit-learn, pytorch, tensorflow and neuralHydrology. I am very interested in extreme events, and the intersection of the analysis of extremes and ML.