Short bio

Mégane is a member of the Deutsche Telekom Chair of Communication Networks (ComNets) since February 2023.

Mégane holds a Master of Science in Electrical Engineering and Information Technology at Karlsruhe Institute of Technology (Germany) as well as an Engineering degree in Signal Processing and Communications at Grenoble Institute of Technology (France). Previously, she has worked for 5 years as at John Deere (European Technology Innovation Center, Germany) and was responsible for several projects on 5G and rural connectivity (“AMMCOA”,”KILANKO”). She is currently responsible for project DAKORE  which aims is to reduce the energy consumption in mobile telecommunication technology.

She works additionally on Compressed Sensing, Network Coding, 5G Campus and Reinforcement Learning.

Contact

Email: megane.gammoudi@tu-dresden.de

Phone: +49 351 463-42114

Room: BAR – I/9

Publications

2024

Tariq, Raazia; Gammoudi, Mégane; Khan, Omer Hanif; Dürrwald, Franz Alwin; Cabrera, Juan A.; Fitzek, Frank H. P.

Using Reinforcement Learning for Optimizing Energy Consumed by Base Stations Proceedings Article

In: IEEE International Conference on Communications, Information, Electronic and Energy Systems (CIEES), Veliko Tarnovo, Bulgaria, 2024.

BibTeX

2023

Gammoudi, Mégane; Scheunert, Christian; Nguyen, Giang T.; Fitzek, Frank H. P.

Practical construction of sensing matrices for a greedy sparse recovery algorithm over finite fields Proceedings Article

In: 2023 Data Compression Conference (DCC), pp. 120-129, Snowbird, UT, USA, 2023.

Links | BibTeX

Gammoudi, Mégane; Cabrera, Juan A.; Fitzek, Frank H. P.

Greedy Algorithm for Compressed Sensing over Finite Fields: Balancing Recovery and Efficiency Proceedings Article

In: European Wireless (EW), Rome, Italy, 2023.

BibTeX