Christopher Ringhofer, M.Sc.

Portrait photo of Christopher Ringhofer in front of a grey/blue background

Short CV

Christopher Ringhofer, M.Sc., works since April 2020 as a researcher and PhD student at the Intelligent 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 the company ithinx GmbH with a focus on the Internet of Things. He received his Master's degree in 2020. In his Master thesis he worked on signal processing of ECG data and its analysis with deep neural networks.

Until 2022 he then worked on two research projects funded by the German Federal Ministry of Education and Research: "KI-Sprung: LUTNet – An energy-efficient AI network of elementary lookup tables" and "KI-LiveS – AI Lab for Distributed and Embedded Systems". Since May 2024, he has been working on another research project funded by the German Federal Ministry of Education and Research called "TransfAIr: Transfer Approaches for Artificial Intelligence in Industry".

Every winter semester, he supervises the lecture and exercise in the Bachelor's course "Embedded Systems". He also taught "AI-based neurosignal processing" as part of a recurring student project.

Research

My current research is on automated search of efficient neural network architectures for signal processing on embedded devices. With the help of evolutionary algorithms I am developing a system that uses neural architecture search to construct latency-optimized networks for signal processing of audio data. I use microcontrollers and embedded FPGAs as target platforms for this. My current use case is digital audio processors, e.g. for studio and live applications.

M. Sc. Christopher Ringhofer

Informatik / AI

Address
Bismarckstr. 90 (BC)
47057 Duisburg
Room
BC 108
Phone
+49 203 379 1986
Fax
+49 203 379 5220
E-Mail
christopher.ringhofer@uni-due.de

Functions

  • Wissenschaftliche/r Mitarbeiter/in, Intelligente Eingebettete Systeme

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
    DOI (Open Access)

    • Book articles / Proceedings papers

  • Ringhofer, Christopher; Gnoss, Alexa; Schiele, Gregor
    Balancing Error and Latency of Black-Box Models for Audio Effects Using Hardware-Aware Neural Architecture Search
    In: Proceedings of the International Conference on Digital Audio Effects, DAFx / International Conference on Digital Audio Effects, DAFx, 3-7 September 2024, Guilford, UK: DAFx, 2024, pp. 65 – 72
  • Kettner, Mark; Perjikolaei, Behnam Razi; Einhaus, Lukas; Ringhofer, Christopher; Qian, Chao; Schiele, Gregor
    FPGA based low latency, low power stream processing AI
    In: 2nd European Workshop on On-Board Data Processing (OBDP2021) / 2nd European Workshop on On-Board Data Processing (OBDP2021), 14-17 June 2021, Online, (Session 3) 2021. Zenodo, 2021
    DOI (Open Access)
  • 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. Piscataway: IEEE, 2021, pp. 320 – 321
    DOI
  • 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.). Cham: Springer, 2021, pp. 327 – 338
    DOI

    • 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),
    2021
    DOI (Open Access)