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Senior Researcher
Group Involvement, NEC Laboratories Europe
IoT Group
Research Interests
Jonathan Fürst is a Senior Researcher in the IoT Platform group at NEC Laboratories Europe. He holds a Ph.D. and a M.Sc. from IT University of Copenhagen (ITU) in Denmark and a B.Eng. in Industrial Engineering from University of Aalen. During his Ph.D., he spent six months as a visiting researcher at UC Berkeley in AMPLab (Software Defined Buildings group). His interests are in the area of IoT cloud-edge systems and practical IoT applications in domains such as smart building & cities. His current research focuses on weakly-supervised machine learning and its adaptation for automated data integration and enrichment.
Publications
- Mccreadie, Richard, John Soldatos, Jonathan Fuerst, Mauricio Fadel Argerich, George Kousiouris, Jean-Didier Totow, Antonio Castillo Nieto et al. "Leveraging data-driven infrastructure management to facilitate AIOps for big data applications and operations." (2021).
- Solmaz, Gürkan, Jonathan Fürst, Samet Aytaç, and Fang-Jing Wu. "Group-In: Group Inference from Wireless Traces of Mobile Devices." In 2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), pp. 157-168. IEEE, 2020.
- Fürst, Jonathan, Mauricio Fadel Argerich, Bin Cheng, and Ernö Kovacs. "Towards knowledge infusion for robust and transferable machine learning in IoT." Open Journal of Internet Of Things (OJIOT) 6, no. 1 (2020): 24-34.
- Argerich, Mauricio Fadel, Jonathan Fürst, and Bin Cheng. "Tutor4RL: Guiding Reinforcement Learning with External Knowledge." In AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (1). 2020.
- Shankari, Kalyanaraman, Jonathan Fuerst, Mauricio Fadel Argerich, Eleftherios Avramidis, and Jesse Zhang. "Mobilitynet: Towards apublic dataset for multi-modal mobility research." Climate Change AI (2020).
- Fürst, Jonathan, Mauricio Fadel Argerich, Kalyanaraman Shankari, Gürkan Solmaz, and Bin Cheng. 2020. Applying weak supervision to mobile sensor data: experiences with transportmode detection. In AAAI-20 Workshop on Artificial Intelligence of Things.
- Cheng, Bin, Jonathan Fuerst, Gurkan Solmaz, and Takuya Sanada. "Fog function: Serverless fog computing for data intensive iot services." In 2019 IEEE International Conference on Services Computing (SCC), pp. 28-35. IEEE, 2019. (Best Paper)
- Fürst, Jonathan, Mauricio Fadel Argerich, Bin Cheng, and Apostolos Papageorgiou. "Elastic Services for Edge Computing." In 2018 14th International Conference on Network and Service Management (CNSM), pp. 358-362. IEEE, 2018.
- Fürst, Jonathan, Kaifei Chen, Hyung-Sin Kim, and Philippe Bonnet. "Evaluating Bluetooth low energy for IoT." In 2018 IEEE Workshop on Benchmarking Cyber-Physical Networks and Systems (CPSBench), pp. 1-6. IEEE, 2018.
- Fürst, Jonathan, Kaifei Chen, Gürkan Solmaz, and Ernö Kovacs. "Automated wireless localization data acquisition and calibration with 6DOF image localization." In Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, pp. 1372-1381. 2018.
- Chen, Kaifei, Jonathan Fürst, John Kolb, Hyung-Sin Kim, Xin Jin, David E. Culler, and Randy H. Katz. "Snaplink: Fast and accurate vision-based appliance control in large commercial buildings." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, no. 4 (2018): 1-27.
- Fürst, Jonathan, Kaifei Chen, Mohammed Aljarrah, and Philippe Bonnet. "Leveraging physical locality to integrate smart appliances in non-residential buildings with ultrasound and bluetooth low energy." In 2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI), pp. 199-210. IEEE, 2016.
Connections
| Google Scholar: | scholar.google.co.uk/citations |
| LinkedIn: | www.linkedin.com/in/jofu87/ |
| https://www.xing.com/profile/Jonathan_Fuerst | |
| GitHub: | https://github.com/jf87 |