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 general, I am interested in the use of advanced machine learning algorithms in climate science, enabling scientific discovery through the use of vast datasets from climate models, satellites and in-situ stations. My research at BAS currently focuses on understanding the drivers of Arctic sea ice loss, with a view to improving the prediction of future sea ice. To this end, I am applying explainable deep learning algorithms with 2D satellite and climate simulation data from the Arctic. More information is available on the project web page.

In 2019 I graduated with a double-first in Information & Computer Engineering from the University of Cambridge. Before graduating, 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.

Research interests

• Explainable deep learning for climate prediction
• Gaussian process modelling for climate forecasting/paleoclimate
• Automatic dating of ice cores

Collaborations

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