Catherine (Cat) Russon
Cat is a health data scientist with an interdisciplinary natural science background. In her PhD she uses machine learning to help patients with type 1 diabetes achieve euglycaemia during exercise.
Cat is driven by both curiosity and a desire to see data science used as a power for good in our communities. Her strengths include an ability to explain complex ideas simply and thriving in a multidisciplinary teams.
In her free time, Cat can be found roaming the mountains, reading a good book or nattering with friends in the pub!
- BSc Liberal Arts and Science, University of Maastricht
- MSc Computer Science, University of East Anglia
Health data science
Interpretable machine learning
Data for good
- Interpolation of 15-minute CGM data to improve the identification of hypoglycaemic episodes
- Machine learning to improve euglycaemia during exercise
- Neural networks to predict overnight hypoglycaemia