Before getting into Machine Learning I studied Physics at Cambridge where I was particularly keen on Statistical and Soft Matter Physics. I then moved to Imperial for my MSc in Artificial Intelligence and picked up an interest for Information Theory and Inference. My master’s thesis was completed in partnership with Prelego (a MedTech startup) and involved building systems for distribution shift adaptation and causal inference for their medical prognosis models. I am keen to continue working at the intersection of healthcare and Statistics/ML research.
When I’m not working, I enjoy cycling, making bread, playing the guitar or listening to Steely Dan.
