I joined the Lamond Laboratory in 2018 to undertake a computational PhD, funded by the Medical Research Council.

My research focuses on investigating how modern machine-learning techniques can enhance the results of mass spectrometry-based proteomics. One of the biggest challenges in doing so, is navigating the “high dimensional, small sample size” problem which is common in ‘omics fields. My project focuses on dimensionality reduction aspects of deep learning which aim to maximise the signal extracted from the data, whilst minimising the number of variables required to characterise said signal.