Olivier Gevaert

Olivier Gevaert is an advisor at Crosscope. Prior to that, they worked as a post-doc at the University of Leuven in Belgium from October 2004 to December 2009. Their research focused on data integration with Bayesian and kernel methods to model biomedical data, such as clinical data, genomic data, transcriptomic data, proteomic data, and metabolomic data. This involved the use of Bayesian networks and support vector machines to model these primary data sources and to investigate data fusion. It also included the integration of secondary publicly available data, such as literature (text mining), protein-protein interactions, pathway databases (KEGG, Biocarta, Reactome, etc.), into their research. Olivier's interest is mostly in oncology, such as breast, ovarian, liver, brain, and (colo)rectal cancer. The primary goal of their research is predicting diagnosis, prognosis or response to therapy. Additional goals are biomarker discovery, drug target discovery and creating fundamentally new hypothesis on molecular biology of cancer.

Olivier Gevaert has a certificate from Stanford Ignite: Powering Innovation and Entrepreneurship at the Stanford University Graduate School of Business. Their PhD is in Electrical Engineering from KU Leuven, and their Master's degrees are in Artificial Intelligence and Electronics from KU Leuven and University College KaHo Sint-Lieven, Ghent, Belgium, respectively.