My current research interest is data efficiency and utility in machine learning, digital agriculture, specifically in the context of: Deep learning, automated image acquisition and image labeling, plant classification, precision agriculture, and high throughput phenotyping. Additional research interests are: The analysis of queueing systems, such as communication networks, smart-grids, caching networks; in particular the methodology of stochastic network calculus that covers a wide range of stochastic arrival processes and schedulers. Wireless sensor networks. I graduated in Mathematics with a Diploma from University of Kaiserslautern with a focus on probability theory in 2010. Afterwards I changed departments to Computer Sciences seeking applications for my theory-knowledge. I received my Ph.D. in Computer Science from University of Kaiserslautern in 2016. Topics of my dissertation were advances in theory and applicability of stochastic network calculus. I followed up my Ph.D. with postdoc-positions at the City University in Hong Kong, at the University of Manitoba, and the University of Winnipeg.