Christopher Ringhofer, M.Sc.
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 signal processing of ECG data and its analysis with deep neural networks. He then worked on two research projects funded by the German Federal Ministry of Education and Research: "KI-Sprung: LUTNet" and "KI-LiveS".
My current work is on automated search of efficient neural network architectures for signal processing on embedded devices. I am developing a system that uses neural architecture search to construct latency-optimized networks for signal processing of audio data. I use embedded FPGAs as the target platform for this. My current use case is digital audio effects, e.g. for studio and live applications.
Past lectures (max. 10)
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.
Elastic AI : System support for adaptive machine learning in pervasive computing systemsIn: CCF Transactions on Pervasive Computing and Interaction Vol. 3 (2021) Nr. 3, pp. 300 - 328ISSN: 2524-5228; 2524-521X
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 - 321ISBN: 978-1-6654-4393-7; 978-1-6654-4394-4
Towards Precomputed 1D-Convolutional Layers for Embedded FPGAsIn: 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 - 338ISBN: 978-3-030-93736-2; 978-3-030-93735-5; 978-3-030-93737-9
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)