Biography
Elizabeth Hayman’s research focuses on developing advanced computational and statistical models to improve the design and performance of biomedical systems. Her DPhil project, Generative Design of Hydrocephalus Shunts, combines high-fidelity finite-element simulations with surrogate machine learning models to accelerate optimisation and design evaluation. By integrating fluid–structure interaction modelling with data-driven methods, her work aims to create computational tools that are both efficient and physiologically realistic. Conducted in close collaboration with clinicians and industrial partners, her research bridges applied mathematics, engineering, and medical science, ensuring that modelling outputs are directly relevant to clinical decision-making and device development.
