Christopher Ringhofer, M.Sc., works since April 2020 as a researcher at the Embedded Systems department of the University Duisburg-Essen. He received his Bachelors Degree for Applied Informatics with a focus on engineering informatics in 2017 at the University Duisburg-Essen. Afterwards he worked three years as a software engineer in a company with a focus on the Internet of Things. He received his Master's degree in 2020. In his Master thesis he worked on the preprocessing of ECG data and its analysis with neural networks.

My current work deals with time-series analysis via artificial intelligence. Specifically, deep learning is used to detect heart conditions in ECG data. Ongoing development of solutions combines concepts of signal processing with neural networks. My further interests in relation to deep learning include attention mechanisms and neural architecture search.

Address
Bismarckstr. 90 (BC)
47057 Duisburg
Room
BC 108

Functions

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

Current lectures

No current lectures.

Past lectures (max. 10)

No past lectures.

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
    ISSN: 2524-5228; 2524-521X
  • Book articles / Proceedings papers

  • 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
    ISBN: 978-1-6654-4393-7; 978-1-6654-4394-4
  • 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
    ISBN: 978-3-030-93736-2; 978-3-030-93735-5; 978-3-030-93737-9