Alison’s work sits at the intersection of engineering, computer science, and healthcare, with a focus on developing simulation and machine learning methods to support complex operational decision-making. Her current research centres on digital twins for healthcare, using computational models to transform clinical workflow data into interpretable and actionable insights. She is particularly interested in patient pathways, emergency care, bed management, and safety-critical healthcare systems where decisions must account for uncertainty, complexity, and limited resources.
Alison’s research emphasises transparency, auditability, and ethical design, ensuring that data-driven tools are not only technically effective but also understandable and trustworthy in practice. Through interdisciplinary collaboration with clinicians, researchers, and health system stakeholders, her work aims to support the safe and responsible use of advanced analytics in real-world healthcare settings.