My PhD will focus on the development of machine learning models for early cancer detection.
Piecewise (segmented) regression analysis used to identify early longitudinal changes in lab test trajectories several years prior to diagnosis. Results form the basis of a manuscript prepared for submission to the British Journal of Cancer.
Development and validation of statistical, classical machine learning, and transformer-based models for early cancer risk prediction using large-scale EHR data. Ongoing work includes data preprocessing, model training, and temporal evaluation.
Investigating the integration of longitudinal EHR data with UK Biobank data to develop a multimodal time-series encoder–transformer for early cancer detection. Current work focuses on study design and data integration, with planned extension to additional modalities such as polygenic risk scores.
For my masters summer project I sped up a novel, exact and tractable machine learning algorithm with parallel multiprocessing under the supervision of Prof Max Little.
At the end of my final year of biomedical science, I had the opportunity to carry out my research project, for which I received a first class grade. It was a great experience to work as part of a team with Prof Melanie Madhani and Dr Kayleigh Griffiths. This project helped me gain practical knowledge and experience working as part of a team leading cutting-edge research in cardiovascular medicine. It also opened my eyes to the opportunity artificial intelligence has to impact many areas of healthcare and biomedical science.
PhD Machine Learning (2024-2028)I started my PhD in October 2024 at Queen Mary University of London. Outcomes for patients with UGI cancers are poor worldwide, with most patients being diagnosed in late stages, so I'm really excited to be working on this highly impactful project.
MSc Computer Science (2023-2024)This year I completed my masters in computer science at the University of Birmingham. This has really sparked my interest in AI and interdisciplinary research in AI healthcare and neuroscience-inspired AI. I've really enjoyed building strong mathematical foundations in ML, which I hope will enable me to be able to think about more complex algorithms, and how they can be improved by ongoing developments in neuroscience.
BSc Biomedical Science (2020-2023)Whilst studying biomedical science at the University of Birmingham, I got to explore a number of topics in areas such as neuroscience, pharmacology and cardiorespiratory sciences. In the final year of my biomedical science undergraduate degree, I was allocated my first choice optional module of neurotrauma. One of the projects I worked on was the bioinformatics analysis of differentially expressed microRNAs in concussion, led by Dr Valentina Di Pietro. Then at the end of my final year of biomedical science, I went on to complete my research project, supervised by Melanie Madhani and Kayleigh Griffiths.