I am a PhD student in the Digital Health Technologies CDT at UCL, with a background in mathematics, computer science, artificial intelligence and machine learning. My current research sits at the intersection of clinical informatics, health data science, and artificial intelligence, with a particular focus on using routinely collected electronic health record (EHR) data to understand variation in treatment and support learning health systems.

My PhD aims to develop an Atlas of Variation for secondary care, inspired by the Dartmouth Atlas of Health Care. Using real-world hospital data, I investigate how treatment decisions vary across patients, clinicians, services, and clinical contexts, and how these patterns can be interpreted to identify opportunities for improving care. I work closely with clinical and research teams at University College London Hospitals NHS Foundation Trust, including projects examining antimicrobial prescribing, treatment pathways, and concordance with clinical guidelines.

Alongside statistical and computational analysis of EHR data, I am interested in exploring how emerging artificial intelligence methods, including large language models and agentic AI systems, can support clinical informatics research and learning health systems.

Ultimately, my research aims to develop data-driven approaches that allow clinicians and healthcare organisations to map, explore, interpret, and learn from treatment variation, creating a stronger feedback loop between routinely collected healthcare data, clinical evidence, and everyday practice.