Said primarily teaches machine learning and computational courses in several master programs: MSc Applied Data Sciences, MSc Epidemiology, Methods and Statistics in the Behavioural, Biomedical, and Social Sciences. The courses include Using data from Routine care, Machine Learning and Applications in Medicine, Computational Statistics, and Computational inference with R. Topics include machine learning classification, clustering, dimension reduction, bootstrapping, numerical optimization and their applications on healthcare data.

Said obtained his MSc Applied Mathematics at TU Delft (2014) and his PhD at Leiden UMC (2020) within the medical statistics group. Currently, he is an assistant professor at the UMC Utrecht on statistics and machine learning for multi-modal data integration. His research topics are high dimensional statistics, latent variable analysis, deep learning, and healthcare digital twins; several MSc projects are available on these topics. He strives to incorporate the latest statistics and machine learning innovations into education and connect it to more ‘traditional’ statistical concepts. He also leads the development of a PhD track Data science for Health within the graduate school of life sciences. Outside of the UMC, you can ask him all about birds and vegetable gardening.