I am a second-year DPhil student in Statistics, working in the broad field of personalised causal inference for digital health. My research focuses on developing dynamic treatment regimes for observational data from health apps, using wearable and smartphone data to deliver robust, personalised recommendations directly to users.

Before joining Oxford, I held an NIHR pre-doctoral research fellowship at UCL, where I also completed my MSc in Statistics. During this time, I developed MCAnalysis, an open-source R and Python package for menstrual cycle analysis. Alongside my research, I competed internationally as a member of the Great Britain Rowing Team. Prior to this, I completed a BSc in Statistics at UCLA on an athletic scholarship.

Heterogeneous effects in health, physiology & wellness 

Dynamic treatment regimes

Statistical Machine learning 

Applied statistics in digital health apps

Causal Inference