Isaac Hayden

Isaac completed an integrated Master’s in Mathematics at Durham University in 2023. While specialising in Riemannian geometry and functional analysis, he also explored the use of neural networks to solve differential equations in his dissertation project. He then worked as a pharmacometric data scientist in a HealthTech start-up delivering precision chemotherapy dosing. There he developed Bayesian pharmacokinetic models to describe drug exposure in special patient populations, and investigated further extensions using machine learning. In October 2024 he joined CEMRG as a PhD student within the Statistics and Machine Learning Centre for Doctoral Training programme at Imperial College London. His research focuses on methods for multifidelity modelling and experimental design to improve translation between animal and human experiments for cardiac safety assessment.