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Polygenic Risk Scores in Haemochromatosis (MSc Project)
Polygenic Risk Scores in Haemochromatosis (MSc Project)
Examined the diverse phenotypic presentation of hereditary haemochromatosis and the limitations of current PRS approaches in predicting iron overload. Identified a haemochromatosis-associated SNP in near-perfect linkage disequilibrium (R² = 0.98) with a variant typically linked to polycythaemia vera, suggesting a shared regulatory mechanism that may help explain discordant clinical phenotypes.
Grammatoppoulos lab, University of Warwick
Machine Learning for Clinical Imaging and Risk Prediction
Machine Learning for Clinical Imaging and Risk Prediction
Built supervised and unsupervised ML classifiers for pneumonia detection from chest X-rays, applying cross-validation, feature extraction, and clinically appropriate metrics (AUC, sensitivity/specificity trade-offs). Also developed stroke-risk prediction models integrating clinical data with hyperparameter tuning and robustness testing, used to critique and propose improvements to the NHS Stroke Pathway.
Ahanathapillai lab, University of Warwick
Embryo Time‑Lapse Imaging and Morphokinetic Modelling
Embryo Time‑Lapse Imaging and Morphokinetic Modelling
Analysed over 1,000 embryo time-lapse videos with more than 100 developmental features to model trajectories and assess embryo-quality prediction. Evaluated temporal markers across patient demographics and explored model architectures for predicting live-birth potential, comparing against existing embryo-selection criteria.
Hartshorne lab, University of Warwick
Meta‑Analysis of Antihypertensive Effects on MSC Function
Meta‑Analysis of Antihypertensive Effects on MSC Function
Conducted a systematic literature review and quantitative meta-analysis on how antihypertensive drugs influence mesenchymal stem cell proliferation, differentiation and signalling. Identified protocol-specific variability and surfaced potential roles for miRNAs in mediating drug-responsive phenotypes.
Boltze lab, University of Warwick
URSS Project: Optimising Rhizobia Inoculants for Legume Nodulation
URSS Project: Optimising Rhizobia Inoculants for Legume Nodulation
Three-month project funded by the Undergraduate Research Support Scheme. Modelled nodulation efficiency across more than 20 Rhizobia strains to identify optimal microbial combinations for improved plant nutrient uptake and crop performance.
Gifford lab, University of Warwick
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