About
My background lies in the field of theoretical physics. In particular, I obtained my Ph.D. in fundamental research on string theory and black holes. Afterward, I decided to pursue research problems with a more immediate application. In that spirit, I did an internship in neurodiagnostics at AMC, where I sought to classify subtypes of Alzheimer's in pathology slides using artificial intelligence methods.
At the NKI I am continuing my interests in deep learning and medical imaging, investigating methodological aspects and applications of, for example, selfsupervised learning and geometrical deep learning.
Last 5 publications

E. Marcus, R. Sheombarsing, J. Sonke, J. Teuwen, "Constrained Empirical Risk Minimization: Theory and Practice", 2023

U. Gürsoy, D. Kharzeev, E. Marcus, K. Rajagopal, C. Shen, "Chargedependent flow induced by electromagnetic fields in heavy ion collisions", Nuclear Physics A, 2021, 1005

C. Couzens, E. Marcus, K. Stemerdink, D. Van De Heisteeg, "The nearhorizon geometry of supersymmetric rotating AdS4 black holes in Mtheory", Journal of High Energy Physics, 2021, 2021;(5)