About
Update 16-07-2019: I am very honored and proud to be awarded a Veni grant! The Veni is a personal grant funded by NWO. With it I will be developing context-aware artificial intelligence for the purpose of improving and enabling new techniques for the analysis of medical image data.
Update 04-07-2019: Per 1 December I will start as assistant professor in geometric machine learning at the University of Amsterdam in the Amsterdam Machine Learning Lab (AMLab) directed by prof. Max Welling. Looking forward to it!
Erik Bekkers is an assistant professor in Geometric Deep Learning in the Machine Learning Lab of the University of Amsterdam (AMLab, UvA). Before this he did a post-doc in applied differential geometry at the dept. of Applied Mathematics at Technical University Eindhoven (TU/e). In his PhD thesis (cum laude, Biomedical Engineering, TU/e), he developed medical image analysis algorithms based on sub-Riemannian geometry in the Lie group SE(2) using the same mathematical principles that underlie mathematical models of human visual perception. Such mathematics find their application in machine learning where through symmetries and geometric structure, robust and efficient representation learning methods are obtained. His current work is on generalizations of group convolutional NNs and improvements of computational and representation efficiency through sparse (graphs) and adaptive learning mechanisms. Erik is a recipient of a MICCAI Young Scientist Award 2018, Philips Impact Award (MIDL 2018) and a personal VENI research grant (awarded by the Dutch Research Council (NWO)).
My CV is available here. An overview of publications is available on my google scholar page, and below (not frequently updated though).
