Foto von Francesca Diedolo

M.Sc. Francesca Diedolo

Technische Universität München

Lehrstuhl für Nachrichtentechnik (Prof. Kramer)


Theresienstr. 90
80333 München


  • Seit Februar 2021 wissenschaftliche Mitarbeiterin am Lehrstuhl für Nachrichtentechnik der TUM
  • M.Sc. in  Communications Engineering an der TUM, 2018-2020
  • B.Sc. in Elektro- und Informationstechnik an der Università degli Studi di Padova, 2015-2018


Angebotene Abschlussarbeiten

Laufende Abschlussarbeiten

Directed Information Graphs


Directed Information Graphs (DIGs) provide a graphical and mathematical framework for studying information flow and causal relationships in complex systems. They find applications in various fields such as communication systems, neuroscience, and causal inference.

A DIG is typically represented as a directed graph, where nodes represent random variables or processes, and directed edges indicate the direction of information flow. In other words, the edges show which variables influence or provide information to other variables.

The student's task is to read and understand the theoretical framework, related algorithms and applications.




  • Diedolo, F.; Böcherer, G.; Schädler M.; Calabrò S.: Nonlinear Equalization for Optical Communications Based on Entropy-Regularized Mean Square Error. European Conference on Optical Communication (ECOC), 2022 mehr… BibTeX
  • Schädler, M.; Böcherer, G.; Diedolo, F.; Calabrò, S.: Nonlinear Component Equalization: A Comparison of Deep Neural Networks and Volterra Series. European Conference on Optical Communication (ECOC), 2022 mehr… BibTeX


  • Böcherer, G.; Diedolo, F.; Pittala, F.: Label Extension for 32QAM: The Extra Bit for a Better FEC Performance-Complexity Tradeoff. 2020 European Conference on Optical Communications (ECOC), IEEE, 2021 mehr… BibTeX Volltext ( DOI )