Karsten Vogt studied Computer Science at the Leibniz University of Hannover. He wrote his Master Thesis on the topic "Detektion regelmäßiger Strukturen durch Level-Set-Segmentierung". Since January of 2010 he has been working toward a PhD degree at the Institut für Informationsverarbeitung which he finished in 2018 on the topic of "Bayessches Transferlernen für die Semantische Segmentierung von Luftbildern". His research interests are machine learning and image processing on remote sensing data with a focus on transfer learning, Markov-Random-Field (MRF) modeling and Markov-Chain-Monte-Carlo (MCMC) sampling methods.