Machine Learning, Artificial Intelligence, Disease Modeling, Reproducible Research.
Sepsis is an undesired whole body inflammatory response to infection and current
diagnostic tools/guidelines are unable to detect its early onset. In cooperation with
Uniklinikum Aachen, our project focusses on the analysis of intensive care patient data in order to identify relevant Sepsis parameters and develop mathematical/hybrid models to facilitate early diagnosis.
|04/2015 - present||Doctoral candidate, Joint Research Center for Computational Biomedicine, AICES, RWTH Aachen University, Germany|
|10/2010 - 11/2013||M.Sc. Student (Communications Engineering), RWTH Aachen Univerity, Germany Thesis: People Detection and Tracking in Crowded Scenes.|
|05/2012 - 09/2012||Internship in Computer Vision, Max-Planck Institute for Informatics|
|09/2011 - 02/2012||Erasmus student, ETH Zurich, Switzerland.|
Doctoral candidate, Joint Research Center for Computational Biomedicine, AICES, RWTH
Aachen University, Germany