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Fakultät für Elektrotechnik und Informationstechnik
Researcher

Melina Geis, M.Sc.

Since August 2021

Part-Time Research Assistant, Communication Networks Institute, TU Dortmund

August 2019 - January 2020

Studies Abroad at Umeå University, Sweden

March 2019 - July 2021

Working Student, QASS GmbH

October 2018 - June 2021

Master, Electrical Engineering and Information Technology, TU Dortmund

July 2018 - September 2018

Internship, QASS GmbH

July 2017 - December 2017

Student Assistant, Communication Technology Institute, TU Dortmund

October 2015 - September 2018

Bachelor, Information and Communication Engineering, TU Dortmund

Publications
07/10/2024

AI-driven Planning of Private Networks for Shared Operator Models

M. Geis, C. Bektas, S. Böcker, C. Wietfeld

In IEEE Symposium on Local and Metropolitan Area Networks (LANMAN), July 2024.

07/10/2024

Automated Private 5G Network Planning for Professional Industries

M. Geis, C. Bektas, S. Böcker, C. Wietfeld

In IEEE Symposium on Local and Metropolitan Area Networks (LANMAN), July 2024.

07/02/2024

AI-based Anomaly Detection for Industrial 5G Networks by Distributed SDR Measurements

K. Šabanović, C. Arendt, S. Fricke, M. Geis, S. Böcker, C. Wietfeld

In IEEE International Symposium on Measurements and Networking (M&N), July 2024.

06/09/2024

Aerial-DRaGon: Machine Learning-based Channel Modeling for Airspace Communication Networks

M. Geis, T. Gebauer, H. Tuna, C. Wietfeld

In IEEE International Conference on Communications (ICC) Workshops, June 2024.

10/02/2023

IndoorDRaGon: Data-Driven 3D Radio Propagation Modeling for Highly Dynamic 6G Environments

M. Geis, H. Schippers, M. Danger, C. Krieger, S. Böcker, J. Freytag, I. Priyanta, M. Roidl, C. Wietfeld

In European Wireless 2023, October 2023.

 

10/12/2022

TinyDRaGon: Lightweight Radio Channel Estimation for 6G Pervasive Intelligence

M. Geis, B. Sliwa, C. Bektas, C. Wietfeld

In 2022 IEEE Future Networks World Forum (FNWF), October 2022.

 

04/13/2022

DRaGon: Mining latent radio channel information from geographical data leveraging deep learning

B. Sliwa, M. Geis, C. Bektas, M. Lopéz, P. Mogensen, C. Wietfeld

In 2022 IEEE Wireless Communications and Networking Conference (WCNC), Austin, Texas