Foto Markus Enzweiler

Informatik und Informationstechnik Prof. Dr. rer. nat. Markus Enzweiler


Campus Esslingen Flandernstraße
Room: F 01.450
Flandernstraße 101
73732 Esslingen

+49 711 397-4272


Laborleitung Labor Signalverarbeitung


Autonomous Intelligent Systems, Robotics, Computer Vision, Deep Learning

special functions

consultation hours

Friday 13:00 - 14:00 (please make an appointment if possible) and whenever my door is open.  



2001 - 2003: Bonn-Rhein-Sieg University of Applied Sciences, undergraduate studies in Computer Science (BSc)

2002 - 2003: York University, Toronto, Centre for Vision Research, undergraduate and graduate studies in Computer Science (BSc, MSc)

2004 - 2005: Ulm University, graduate studies in Computer Science (BSc)

2006 - 2011: Heidelberg University, doctorate degree at the Faculty of Mathematics and Computer Science (Dr. rer. nat.)

2010 - 2021: Daimler AG / Mercedes-Benz AG Research & Development, sensor-based environment perception for driver assistance systems and autonomous driving 

Since 03/2021: Professor for Autonomous Mobile Systems at Esslingen University of Applied Sciences

Since 2023: Director of the Institute for Intelligent Systems


2003 - 2009: Scholar of the Studienstiftung des deutschen Volkes (German National Merit Foundation)

2012: IEEE intelligent Transportation Systems Society, Best PhD Dissertation Award

2012: Uni-DAS Research Award for an outstanding PhD thesis in the field of driver assistance systems

2013: German Association for Pattern Recognition, Main Prize

2014: Junior-Fellow of the German Informatics Society (GI – Gesellschaft für Informatik)

2014: IEEE Intelligent Transportation Systems Society, Outstanding Application Award

2014: IEEE Intelligent Vehicles, Best Paper Award

2016: IEEE Intelligent Vehicles, Best Paper Award

2017: IGD Fraunhofer, Best Paper Award "Impact on Business"



Please refer to Google Scholar.

more information

Please contact me regarding student projects and theses in the fields of autonomous systems, computer vision, and deep learning.  

Personal webpage:


Interested? Apply now! for the wintersemester 2024/2025