Short CV

Lukas Einhaus, M.Sc. works since April 2020 as a researcher and PhD student at the Embedded Systems department of the University of Duisburg-Essen. After his Bachelors thesis about programming abstractions for concurrent embedded systems he received his Masters degree with a focus on distributed, reliable systems at the University Duisburg-Essen. In his Masters thesis he did research on quantizing neural networks.


My research focuses on techniques for designing neural networks that allow for an efficient implementation in hardware, especially on FPGAs. My main interest herein lies on so called quantized or low precision neural networks. These differ from conventional full precision networks in the heavily reduced bit depth used for computational operations or the representation of the information flow.

Bismarckstr. 90 (BC)
47057 Duisburg
BC 104


  • Wissenschaftliche/r Mitarbeiter/in, Eingebettete Systeme der Informatik

The following publications are listed in the online university bibliography of the University of Duisburg-Essen. Further information may also be found on the person's personal web pages.

    Journal articles

  • Cichiwskyj, Christopher; Schmeißer, Stephan; Qian, Chao; Einhaus, Lukas; Ringhofer, Christopher; Schiele, Gregor
    Elastic AI : System support for adaptive machine learning in pervasive computing systems
    In: CCF Transactions on Pervasive Computing and Interaction Vol. 3 (2021) Nr. 3, pp. 300 - 328
  • Book articles / Proceedings papers

  • Qian, Chao; Einhaus, Lukas; Schiele, Gregor
    ElasticAI-Creator: Optimizing Neural Networks for Time-Series-Analysis for On-Device Machine Learning in IoT Systems
    In: Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems (SenSys 2022) / 20th ACM Conference on Embedded Networked Sensor Systems (SenSys 2022): 6 - 9 November 2022; Boston, USA / Gummeson, Jeremy; Lee, Sunghoon Ivan (Eds.) 2022, pp. 941 - 946
  • Einhaus, Lukas; Qian, Chao; Ringhofer, Christopher; Schiele, Gregor
    In-Situ Artificial Intelligence for Self-∗ Devices : The Elastic AI Ecosystem (Tutorial)
    In: 2nd IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2021: Proceedings / 2nd IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2021, Virtual, Washington, 27 September - 1 October 2021 2021, pp. 320 - 321
  • Einhaus, Lukas; Qian, Chao; Ringhofer, Christopher; Schiele, Gregor
    Towards Precomputed 1D-Convolutional Layers for Embedded FPGAs
    In: Machine Learning and Principles and Practice of Knowledge Discovery in Databases: Proceedings, Part I / International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021 / Kamp, Michael; Koprinska, Irena; Bibal, Adrien; Bouadi, Tassadit; Frénay, Benoît; Galárraga, Luis; Oramas, José.; Adilova, Linara; Krishnamurthy, Yamuna; Kang, Bo; Largeron, Christine; Lijffijt, Jefrey; Viard, Tiphaine; Welke, Pascal; Ruocco, Massimiliano; Aune, Erlend; Gallicchio, Claudio; Schiele, Gregor; Pernkopf, Franz; Blott, Michaela; Fröning, Holger; Schindler, Günther; Guidotti, Riccardo; Monreale, Anna; Rinzivillo, Salvatore; Biecek, Przemyslaw; Ntoutsi, Eirini; Pechenizkiy, Mykola; Rosenhahn, Bodo; Buckley, Christopher; Cialfi, Daniela; Lanillos, Pablo; Ramstead, Maxwell; Verbelen, Tim; Ferreira, Pedro M.; Andresini, Giuseppina; Malerba, Donato; Medeiros, Ibéria; Fournier-Viger, Philippe; Nawaz, M. Saqib; Ventura, Sebastian; Sun, Meng; Zhou, Min; Bitetta, Valerio; Bordino, Ilaria; Ferretti, Andrea; Gullo, Francesco; Ponti, Giovanni; Severini, Lorenzo; Ribeiro, Rita; Gama, João; Gavaldà, Ricard; Cooper, Lee; Ghazaleh, Naghmeh; Richiardi, Jonas; Roqueiro, Damian; Saldana Miranda, Diego; Sechidis, Konstantinos; Graça, Guilherme (Eds.) 2021, pp. 327 - 338
  • Posters / Proceedings posters

  • Helms, Domenik; Kettner, Mark; Perjikolaei, Behnam Razi; Einhaus, Lukas; Ringhofer, Christopher; Qian, Chao; Schiele, Gregor;
    FPGA based low latency, low power stream processing AI
    2nd European Workshop on On-Board Data Processing (OBDP2021), 14-17 June 2021, Online, (Session 3),