Current Staff Members

Fabian Scheidt

Member of the Signal Processing Group and the Robust Data Science Group at the Institute of Telecommunications, TU Darmstadt.


work +49 6151 16-22534
fax +49 6151 16-21342

Work S3|06 30
Merckstraße 25
64286 Darmstadt

Office Hours: upon request

Fabian graduated from TU Darmstadt with a BSc. and MSc. in Industrial- and Electrical Engineering and Information Technology, with research specialization in communication technology and sensor systems (KTS). His BSc. was with the Signal Processing Group in the field of fast cooperative localization in distributed wireless sensor networks (2016). His MSc. were twofold: First with the Chair of Econometrics in the field of Statical Learning methods for Churn Analysis in Telecommunication Industries (2020). Second with the Robust Data Science Group at Robust and Computationally Efficient Statistical Learning in High-Dimensional Data: The T-Rex Selector (2023).

In May 2023 he joined the Signal Processing and Robust Data Science groups and is affiliated with the German federal BMBF Cluster4Future initiative curATime under the curAISig project. It is a joint research project with the University Medical Center Mainz: Klinische Epidemiologie und Systemmedizin, Centrum für Thrombose und Hämostase (CTH).

The projects aims are:

  • Development of robust signal processing methods for heart-rate variability (HRV) analysis
  • Development of statistical learning methods for high-dimensional bio-database analysis
  • The discovery of novel and reproducible bio-marker signatures
  • Enablement of leap innovations in precision diagnostics and individualized therapies
  • Integration of innovative technologies into system oriented biomedical research

Industrial Experience:

  • 2019-2022 Research and Innovation at Deutsche Telekom in positions as:
    • Data Engineer: development of data pipelines aiming for the creation of a comprehensive Big Data set of DT’s Radio Access Network in Germany, as well as in the data aggregation and evaluation of massively distributed sensor networks. Also, data modeling with methods of the field of data driven engineering and statistical learning.
    • Technometrician: applied land site classification, remote sensing, statistical analysis of landsite, and geo-location data along with socio-economics data
  • 2018-2019 Research Intern in Signal Processing and Operations Management at ABB Corporate Research
    • Signal processing and data-driven engineering for maintenance of gearless mill drives.


  • False Discovery Rate Control in High-Dimensional Variable Selection and Ensemble Learning
  • Stochastic Signal Processing and Time Series Analysis
  • Detection and Estimation Theory
  • Sparse Coding, Dictionary Learning
  • Intelligent Sensorial Systems and Graph Based Learning
  • High Performance Computing and Efficient Algorithms

Programming Interests: C++, Python, R, MATLAB

Open Student Projects

Please shoot me an if you want to learn more about the currently available topics for student projects (pro and project seminars, bachelor's and master's theses).


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