Academic Biography
I am a Doctoral Scholar funded by the NERC UKRI Environmental Research Scholarship. I have a First Class BEng Engineering Degree, and the Institute of Civil Engineers Award (2020), and a Master's of Science degree in Water Science, Policy and Management (2021). I am in the fourth year of a four year DPhil/PhD course in across Atmospheric, Planetary and Oceanic Physics and the School of Geography and the Environment.
I and am co-supervised by Professor Hannah Christensen, Professor Louise Slater, 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.