I’m a PhD candidate in the AIC group at Southampton University and an enrichment student at The Alan Turing Institute, supervised by Long Tran-Thanh and Corina Cirstea from Computer Science and Ruben Sanchez-Garcia from Mathematics. My research aims to combine tools from topological data analysis with machine learning to enable topology-driven deep learning. Our paper Hypothesis classes with a unique persistence diagram are nonuniformly learnable provides the first learning theoretic justification for the inclusion of persistence-based terms in loss functions, and was presented as a spotlight presentation at the TDA and Beyond NeurIPS 2020 workshop.
Before starting my PhD, I earned a Mathematics MSci from the University of Birmingham. My masters project, The Persistent Homology of Complexes from Point Data Sets, studied the algebraic topology underpinning topological data analysis.
My CV details my work experience, which includes developing an end-to-end data science pipeline for an automotive start-up and leading a team of edtech developers implementing automated mathematical assessments.
September 2021: I have started as enrichment student at The Alan Turing Institute.
July 2021: I chaired the organising committee for AIC Conference 2021.
July 2021: I am attending London Geometry and Machine Learning 2021 summer school.
December 2020: Our spotlight presentation at the TDA and Beyond workshop is now available.
October 2020: Two papers accepted to the NeurIPS 2020 TDA and Beyond workshop!