Yvan Saeys graduated as a computer scientist from Ghent University in 2000, and obtained his PhD in computer science at the Bioinformatics group of the Flemish Institute for Biotechnology (VIB) and Ghent University. After spending time abroad at the University of the Basque Country (Spain) and the Université Claude Bernard (Lyon 1, France), he established the DAMBI research group at the Inflammation Research Centre (IRC), focusing on the development and application of new data mining and machine learning techniques for biomedicine. Yvan Saeys is professor of Machine Learning at Ghent University, and PI in Systems Immunology at VIB. He is developing state-of-the-art data mining and machine learning methods for biological and medical applications, and is an expert in computational models to analyze high-throughput single-cell data. The methods he develops have been shown to outperform competing techniques, including computational techniques for regulatory network inference (best performing team at the DREAM5 challenge) and biomarker discovery from high-throughput, single cell data (best performing team at the FlowCAP-IV challenge). Yvan Saeys has published >100 papers in top ranking journals and conferences, and his work has been cited more than 9500 times.