athina spiliopoulou
picture of Athina Spiliopoulou

About me

I am a Chancellor's Fellow in Data-Driven Innovation at the Usher Institute of Population Health Sciences and Informatics, at the University of Edinburgh. I have formal training in machine learning and ten years' research experience in statistical genetics and molecular epidemiology.

I am a member of the Molecular Epidemiology group (Usher Institute) and the Centre for Statistics (School of Mathematics) and I hold a research affiliation with the Centre for Genomic and Experimental Medicine at the Institute of Genetics and Cancer.


My research aims to address questions about the pathogenesis, progression and treatment of disease by developing and applying statistical methods to perform predictive and causal inferences. A key component of my work is the analysis of large-scale, multi-source and high-dimensional datasets, combining genetic and biomarker data (omics) with electronic or conventionally collected health records.

I have mainly focused on applications of precision medicine on autoimmune diseases. The goal is to stratify individuals based on genetic or biomarker signatures that distinguish different subtypes of disease, and to develop corresponding predictive and prognostic biomarkers. Predictive biomarkers of treatment response enable targeting of treatments to the group of patients most likely to respond. Similarly, prognostic biomarkers can enhance disease management, such as screening for complications and recruiting for clinical trials, by identifying patients with a worse disease outlook.