Stelios Boulitsakis Logothetis

Stelios is a PhD student in the Cardiovascular Epidemiology Unit, supervised by Professor Angela Wood. He is funded by the HDR UK Big Data for Complex Disease Driver Programme, and his PhD investigates developing dynamic risk prediction models to target concomitant diseases and their interactions. Stelios completed his MEng in Computer Science at Durham University. His dissertation investigated estimating acute medical patients' short-term risk of deterioration using interpretable machine learning. Prior to beginning his PhD, Stelios gained industry experience through roles in data science R&D at Evergreen Life, and software engineering at Deutsche Bank. Additionally, his research on predicting Accident & Emergency (A&E) admissions and readmissions using explainable machine learning has been recognised and endorsed by the National Institute for Health Research (NIHR) and formed part of a Department of Health and Social Care policy briefing on addressing winter pressures in the NHS and also won the best talk award at the Society for Acute Medicine International Conference 2023.

Stelios email address is sb2690@medschl.cam.ac.uk