Short bio

Mégane is a PhD researcher at the Deutsche Telekom Chair of Communication Networks (ComNets) at TU Dresden since February 2022.

She 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 4 years as a research engineer at John Deere (European Technology Innovation Center, Germany) and contributes to several research projects on 5G and rural connectivity (“AMMCOA”,”KILANKO”). She is currently contributing to the project DAKORE  which aims is to reduce the energy consumption in mobile telecommunication technology.

Her research interests are Compressed Sensing, Network Coding and 5G Campus.



Phone: +49 351 463-42114

Room: BAR – I/9

Research activities

  • Compressed Sensing
  • Network Coding
  • NFV/SDN, Network Slicing, 5G Campus
  • Network Simulation
  • Reinforcement learning


Master Thesis

  • Virtual Testbed Implementation for Investigating Network Slicing (Anusha Umesh, Darmstadt University of Applied Sciences)
  • Optimization of Network Architecture for Tomorrow’s Agriculture (Jeyashree Nirmalvasan Padmapriya, Darmstadt University of Applied Sciences)

Student Thesis

  • Researching, testing, and implementing of IoT and automation technologies (Patrick Marschall, TU Kaiserslautern)



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.