Angeliki is a data scientist with a strong background in computer science and data analytics. She holds a BSc in Computer Science and an MSc in Advanced Computer Science (Data Analytics) from the University of Leeds, graduating with distinction. Her academic journey equipped her with expertise in data science, machine learning, and deep learning, which she has applied across various domains including healthcare, energy, and logistics.

Her career began with software engineering and data-focused internships, where she contributed to system optimisation and data-driven decision-making. These experiences sparked a deeper interest in data science and its real-world applications, particularly in the public sector and healthcare.

Angeliki’s research interests lie in the application of data science to healthcare, with a focus on improving patient outcomes and promoting health equity. She is particularly interested in using predictive modelling and data-driven insights to identify risks, understand patterns in patient care, and support evidence-based decision-making.

Currently, Angeliki is a Data Scientist at the Leeds Institute for Data Analytics (LIDA). Her recent work focused on healthcare, collaborating with Yorkshire Ambulance Services to develop models that identify patient safety risks and highlight care inequalities, aiming to support more equitable and effective health outcomes.

Over the next six months, Angeliki will work on the Analysing Property-based Illegal Drug Market Location Choices project at the Vulnerability & Policing Futures Research Centre. She will use area-level data and econometric modelling to identify factors influencing where offenders establish drug market hubs, supporting efforts to inform prevention and policing strategies.