Solon is studying for a PhD in Biostatistics at the MRC Biostatistics Unit, University of Cambridge. Before starting his PhD, he completed an MSc in Statistics at KU Leuven focusing on the Biometrics track and has worked as Research Scientist at the MRC Biostatistics Unit (2016-2017).
Solon's interests lie in developing statistical machine learning methods applied to medicine and healthcare. His main research focuses on tailored Bayesian inference for binary outcomes when different misclassification errors incur different penalties. This is often the case when making decisions around treatments with known side effects where model estimation benefits from incorporating this information. This is also relevant in the diagnostic medical context where for example, missing a disease is usually more severe than a falsely detecting a disease.
He is particularly interested (Generalised) Bayesian methods, (risk) prediction modeling, (medical) decision making and computationally intensive methods.
Bayesian methods, Biostatistics, Machine learning, Statistical learning