Melina Geis, M.Sc.
Since August 2021
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
- Machine Learning for Communication Networks
- Radio Propagation Modeling
- Network Planning
- 5G / 6G
Publications
09/01/2025
Leveraging Transfer Learning for Rapid Adaptation of ML-Based Indoor Propagation Models
M. Geis, N. Faust, H. Schippers, S. Böcker, C. Wietfeld
In IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
04/22/2025
DoNext: An Open-Access Measurement Dataset for Machine Learning-Driven 5G Mobile Network Analysis
H. Schippers, M. Geis, S. Böcker, C. Wietfeld
In IEEE Transactions on Machine Learning in Communications and Networking, April 2025.
12/08/2024
REMIBRANDT: Imputing Radio Environmental Maps for Safety-Critical Applications with Machine Learning
N. Altenburg, H. Schippers, M. Geis, C.Wietfeld
In IEEE Globecom Workshops (GC Wkshps), Cape Town, South Africa, Dec. 2024.
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