Lukas Jünger

Thesis & Student Jobs

Students interested in a BSc/MSc thesis or a HiWi job are asked to make an appointment via email or to personally visit me at the institute. Open positions can be found here.

My student jobs focus on low-level software (e.g. Linux) and hardware modeling using SystemC. If you would like to learn more in this area, contact me.


Student assistants:

  • Simon Winther

Bachelor students:

  • Antonios Salios


Lukas Jünger received his B.Sc. and M.Sc. degree in Electrical Engineering from RWTH Aachen University in 2015 and 2018 respectively. Since 2018, he is a PhD student at the Institute of Communication Technologies and Embedded Systems under the supervision of Prof. Rainer Leupers. His research focus is the modeling and simulation of heterogeneous multi-processor computer systems.


Zurstraßen, N., Jünger, L., and Kogel, T., Keding, H. and Leupers, R.: AMAIX In-Depth: A Generic Analytical Model for Deep Learning Accelerators, in International Journal of Parallel Programming, 2022, 10.1007/s10766-022-00728-3

Jünger, L., Bianco, C., Niederholtmeyer, K., Petras, D. and Leupers, R.: Optimizing Temporal Decoupling using Event Relevance, in Proceedings of the Asia South Pacific Design Automation Conference (ASP-DAC), 2021, 10.1145/3394885.3431419

Jünger, L., Bölke, J., Tobies, S., Hoffmann, A. and Leupers, R.: ARM-on-ARM: Leveraging Virtualization Extensions for Fast Virtual Platforms, in Proceedings of the Conference on Design, Automation & Test in Europe (DATE), pp. 1508-1513, 2020, 10.23919/DATE48585.2020.9116573 ©2020 IEEE

Jünger, L., Zurstraßen, N., Kogel, T., Keding, H. and Leupers, R.: AMAIX: A Generic Analytical Model for Deep Learning Accelerators, in SAMOS International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation, pp. 36-51, Springer, 2020, 10.1007/978-3-030-60939-9_3

Jünger, L., Weinstock, J. H., Leupers, R. and Ascheid, G.: Fast SystemC Processor Models with Unicorn, in Proceedings of the 2019 Workshop on Rapid Simulation and Performance Evaluation: Methods and Tools, Jan. 2019, 10.1145/3300189.3300191