Chao Qian, M. Sc.
Short CV
Chao Qian, M.Sc., has been working as a researcher and PhD student at the UDE's Department of Embedded Systems since April 2020. He received his bachelor's degree in Electronic Engineering at the University of Electronic Science and Technology of China in 2015 with a focus on wireless sensor networks. From 2013 to 2017, he was working in a company designing and producing wearable devices and humanoid robots. In 2020, he received his master's degree in Embedded Systems with a focus on energy-efficient embedded AI systems at the University Duisburg-Essen.
Research
At the core of his research interests are techniques that allow artificial intelligence (AI) in reconfigurable hardware such as FPGAs that can operate with high energy efficiency and allow to design high-performance hardware with proper software components. A special focus lies in introducing AI technologies into more areas of the widely applied domain of embedded systems which traditionally were not capable of running AI due to limited computing resources and power budget.
47057 Duisburg
Functions
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Wissenschaftliche/r Mitarbeiter/in, Eingebettete Systeme der Informatik
Current lectures
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.
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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)Online Full Text: dx.doi.org/ (Open Access) -
ElasticAI : Creating and Deploying Energy-Efficient Deep Learning Accelerator for Pervasive ComputingIn: 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) / PerCom 2023, 13-17 March 2023, Atlanta, GA, USA 2023, pp. 297 - 299Online Full Text: dx.doi.org/
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Enhancing Energy-Efficiency by Solving the Throughput Bottleneck of LSTM Cells for Embedded FPGAsIn: Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part I / International Workshops of ECML PKDD 2022, Grenoble, France, September 19–23, 2022 / Koprinska, Irena; Mignone, Paolo; Guidotti, Riccardo (Eds.) 2023, pp. 594 - 605Online Full Text: dx.doi.org/
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ElasticAI-Creator: Optimizing Neural Networks for Time-Series-Analysis for On-Device Machine Learning in IoT SystemsIn: 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 - 946Online Full Text: dx.doi.org/ (Open Access)
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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 - 321Online Full Text: dx.doi.org/
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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 - 338Online Full Text: dx.doi.org/
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An Embedded CNN Implementation for On-Device ECG AnalysisIn: IEEE Annual Conference on Pervasive Computing and Communications Workshops (PerCom) / PerIoT 2020: The Fourtternational Workshop on Mobile and Pervasive Internet of Thingsh In 2020Online Full Text: dx.doi.org/
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Time to Learn : Temporal Accelerators as an Embedded Deep Neural Network PlatformIn: IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning: Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020 ; Ghent, Belgium, September 14-18, 2020 ; Revised Selected Papers / 2nd International Workshop on IoT Streams for Data-Driven Predictive Maintenance ; IoT Streams 2020 ; September 14-18, 2020, Ghent, Belgium / Gama, João; Pashami, Sepideh; Bifet, Albert; Sayed-Mouchaweh, Moamar; Fröning, Holger; Pernkopf, Franz; Schiele, Gregor; Blott, Michaela (Eds.) 2020, pp. 256 - 267Online Full Text: dx.doi.org/
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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 - 328Online Full Text: dx.doi.org/ (Open Access)