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I am a UK Research and Innovation (UKRI) Innovation Fellow funded by Health Data Research UK. I work closely with clinical collaborators across King’s Health Partners applying machine learning to patient records at scale. My research develops machine learning methods based on knowledge graphs that combine large public datasets with health records to predict and explain patient outcomes. The focus is on delivering real world clinical value through multiple clinical collaborations including atrial fibrillation management, patient flow, adverse drug reactions, cancer subtyping and kidney failure. I did my PhD at Cambridge University where I worked on applying systems biology methods to neurodegenerative disease, then I joined the Dobson group at KCL in 2016 as a postdoctoral research fellow in the National Institute for Health Research Maudsley Biomedical Research Centre (NIHR Maudsley BRC). 

Research Interests:

  • Using knowledge graphs to improve machine learning performance
  • Putting machine learning into clinical practice with explainability and real-time support
  • Natural language processing methods for clinical text
  • Modelling patient trajectories (PhD supervision)