PhD student in the research training programm Towards Graduate Experts in Photonic Quantum Technologies (GRK2642)
Project 2: Sensing of weak non-stationary signals with an integrated magneto-optical quantum sensor
Project 5: Quantum photonics enhanced by machine-learning tools
Research group Optomechatronics
- Corcione E, Pfezer D, Hentschel M, Giessen H, Tarín C. Machine Learning Methods of Regression for Plasmonic Nanoantenna Glucose Sensing. Sensors. 2022; 22(1):7. https://doi.org/10.3390/s22010007
- A. Karim, E. Corcione, J. Jäger and A. Verl, "Experimental determination of compliance values for a machining robot", 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Auckland, New Zealand, 2018, pp. 1311-1316, doi: 10.1109/AIM.2018.8452434.
- Since 04/2021
Research Assistant at the Institute for System Dynamics
- 05/2020 - 10/2020
Internship at Festo SE & Co. KG in the department "Process Automatisation"
- 10/2018 - 03/2021
- Master "Technical Cybernetics" at University of Stuttgart
- 04/2018 - 07/2018
Research Associate at University of Auckland
- 10/2014 - 03/2018
- Bachelor "Technical Cybernetics" at University of Stuttgart