Biography

I am a Data Scientist at the BAS Artificial Intelligence Lab (AI Lab), supervised by Dr Scott Hosking and funded by the Alan Turing Institute’s AI for Science programme. In my work, I aim to enable scientific progress through the application of machine learning algorithms to large datasets from climate models, satellites, and in-situ stations. I am currently developing a deep learning-based Arctic sea ice forecasting AI, ‘IceNet’ (initial study published in Nature Communications). My other research work involves combining satellite and surface data to inform weather sensor placement in Antarctica (more information on the project webpage).

Before BAS, I studied Information & Computer Engineering at Cambridge University, graduating with a double-first. My Master’s research at the Computational & Biological Learning Lab involved the development of a machine learning algorithm for automatically dating ice cores based on seasonally-dependent ice core chemicals. My thesis, ‘GPCore: A Gaussian Process Approach for Inferring Ice Core Chronologies’, was awarded a Distinction and is available on my GitHub.

Supervisory positions:

• Co-supervisor of Ellie Krige’s Cambridge University MSci project: ‘Using IceNet to predict and understand the freeze-up and break-up dates of sea ice in Hudson Bay, Canada’ (1st class)

Research interests

• Explainable deep learning for climate prediction
• Arctic sea ice forecasts for conservation and ecosystem management
• Combining gridded climate data with off-grid surface station observations

Collaborations

Alan Turing Institute (ATI) | Computational and Biological Learning Lab (CBL), University of Cambridge | UCL Centre for Artificial Intelligence | WWF