Jakob Schwalb-Willmann just started his M.Sc. thesis titled “A deep learning movement prediction model using environmental data to identify movement anomalies”. He will combine animal movement and remote sensing data in order to develop a generic, data-driven DL-based model that predicts movements from movement history alongside environmental covariates in order to detect movement anomalies. He will establish simulated, controlled environments that allow precise adjustments of the model inputs to test the model’s feedbacks and its variability. It can be considered as a precursor study for the model’s deployment on real data and to only experimentally apply it on such due to the given constraints (time and content) of his M.Sc. thesis. The first supervisor is Dr. Martin Wegmann.
EAGLE Innolab Presentation: Post-processing and Quality Assessment of Mapathon-Derived Mining Data for Cobalt Belt Mapping
On August 11, 2026, Espérance Kandjale will present her Innolab results on " Post-processing and Quality Assessment of Mapathon-Derived Mining Data for Cobalt Belt Mapping " at 12:00 in seminar room 3, John-Skilton-Str. 4a. From the abstract: During my internship, I...
![[spotlight] Lecturer Spotlight: Martin Wegmann](https://eagle-science.org/wp-content/uploads/2026/07/Martin_Wegmann_EAGLE_lecture_2026-400x250.jpg)
