Isaac completed an integrated Master’s in Mathematics at Durham University in 2023. While specialising in geometry and functional analysis, he also explored the use of neural networks to solve differential equations in his dissertation project. Before joining StatML, he worked as a pharmacometric data scientist for a HealthTech start-up delivering precision drug dosing. There he developed nonlinear mixed-effects models to describe drug exposure and optimise doses in special patient populations, while investigating further extensions using machine learning. On the StatML programme, he is interested in exploring the integration of machine learning models like Gaussian processes and variational autoencoders into classical statistical models for various healthcare applications. In his spare time, he enjoys climbing, running and learning languages.
Isaac Hayden
