DoMars16k: A Diverse Dataset for Weakly Supervised Geomorphologic Analysis on Mars. - Thorsten Wilhelm; Melina Geis; Jens Püttschneider; Timo Sievernich; Tobias Weber; Kay Wohlfarth; Christian Wöhler (Remote. Sens., 2020)

TinyDRaGon: Lightweight Radio Channel Estimation for 6G Pervasive Intelligence. - Melina Geis; Benjamin Sliwa; Caner Bektas; Christian Wietfeld (FNWF, 2022)

DRaGon: Mining Latent Radio Channel Information from Geographical Data Leveraging Deep Learning. - Benjamin Sliwa; Melina Geis; Caner Bektas; Melisa López; Preben Mogensen 001; Christian Wietfeld (WCNC, 2022)

REMIBRANDT: Imputing Radio Environmental Maps for Safety-Critical Applications with Machine Learning. - Nils Altenburg; Hendrik Schippers; Melina Geis; Christian Wietfeld (GLOBECOM (Workshops), 2024)

Aerial-DRaGon: Machine Learning-based Channel Modeling for Airspace Communication Networks. - Melina Geis; Tim Gebauer; Harun Tuna; Christian Wietfeld (ICC Workshops, 2024)

AI-Based Anomaly Detection for Industrial 5G Networks by Distributed SDR Measurements. - Kevin-Ismet Sabanovic; Christian Arendt; Steffen Fricke; Melina Geis; Stefan Böcker; Christian Wietfeld (M&N, 2024)

Automated Private 5G Network Planning for Professional Industries. - Melina Geis; Caner Bektas; Stefan Böcker; Christian Wietfeld (LANMAN, 2024)

AI-Driven Planning of Private Networks for Shared Operator Models. - Melina Geis; Caner Bektas; Stefan Böcker; Christian Wietfeld (LANMAN, 2024)