I am a Data Scientist specializing in cancer epidemiology, spatial statistics, and predictive modelling. My research focus centers on utilizing large-scale, population-based registries to understand disease incidence, evaluate health inequalities, and support evidence-based public health policy. Currently, I am a Research Intern mentored by Dr David Muller as part of the 2025 cohort of the HDR UK Health Data Science BIP within the Cancer Epidemiology and Prevention Research Unit (CEPRU) at Imperial.

My research addresses the intersection of computational statistics and population health, specifically: 

• Cancer Surveillance & Outcomes: Quantifying long-term cancer incidence patterns using multi-country registry datasets (IARC CI5) to identify critical trends in prostate and colorectal cancers.
• Health Inequalities: Investigating how socioeconomic and ethnic backgrounds relate to cancer stage at diagnosis and patient characteristics using large-scale linked datasets.
• Spatial Epidemiology: Developing modular geospatial workflows to examine demographic and social patterns across high-density populations, utilizing R-based tools like sf and tmap.
• Bayesian & Longitudinal Modelling: Applying Bayesian hierarchical models and spline-based methods to account for completeness variation and age-structure inconsistencies in population registries.