Chao Qian, M. Sc.
Chao Qian, M.Sc. has been working as a researcher and PhD student at the "Embedded Systems" group of the University Duisburg-Essen 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 network. 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 of embedded AI systems at the University Duisburg-Essen.
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 here lies in introducing AI technologies into more areas of the widely applied domain of embedded systems with its limited computing resources and power budget.
No 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.
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 2020
ISBN: 978-1-7281-4716-1; 978-1-7281-4717-8
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 - 267
ISBN: 978-3-030-66769-6; 978-3-030-66770-2
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 - 328
ISSN: 2524-5228; 2524-521X