I am a machine learning engineer with a passion for developing software solutions to tackle contemporary healthcare challenges. I have obtained my PhD in Engineering Science at KU Leuven with summa cum laude distinction in 2015. During my PhD, I developed a fully automated case-finding tool for type 2 diabetes based on Belgian health expenditure data. In contrast to most existing methods, the approach we developed can be scaled to population-wide use at negligible operational cost. My PhD research is summarized in my thesis "Machine Learning on Belgian Health Expenditure Data - Data-driven Screening for Type 2 Diabetes". From a machine learning perspective, my research emphasizes predictive modelling with uncertainty and automation of the learning process, specifically semi-supervised classification, large-scale learning and hyperparameter optimization. I am an open-source software enthusiast focused on designing reusable components using multiple programming paradigms.
I am passionate about programming and machine learning and I particularly love to apply my skills to challenging problems that matter. I want to use my knowledge to contribute to projects with the potential to positively affect many people. I am currently a post-doctoral researcher at the STADIUS lab of KU Leuven, where I focus on applying machine learning in several interdisciplinary projects within the healthcare domain.