The visual data analysis group has topics for student theses/projects in computer science and related disciplines (also including meteorology and climate sciences) available (B.Sc./M.Sc. theses etc.). If you are interested in issues concerning visual data analysis, in particular with application to geoscientific challenges (e.g., weather forecasting, climate research), please contact Dr. Marc Rautenhaus. Topics cover a range of computer graphics, data analysis and visualization issues, including, e.g., 3D rendering and uncertainty visualization. They mostly include work with our open-source 3D ensemble visualization tool "Met.3D" and will be tailored to the student's interests and background.
Currently available theses topics (MSc/BSc) include:
- "Visual analysis of feature relations". We are interested in developing visual analysis techniques that facilitate the analysis of relations of 3D features in atmospheric simulation data. As a simple example: What is the distance between two isosurfaces of interest, and how does this distance develop over time? We will consider more complex features and relations, though. Required skills: Very good programming skills, preferrably in C++/OpenGL/Python, and knowledge in visualization and/or computer graphics.
Recently completed theses include:
Vogt, Thorwin, 2022: Real-time direct-volume-rendering for visualization of numerical weather forecasts
Elwart, Luka, 2022: Cloud Rendering using Dynamic Lights in Met.3D
Laugwitz, Anton, 2022: Vergleich von numerischen Wetterprognosen unter Verwendung von Bildmerkmalen
Bender, Paul, 2022: CNN based Segmentation of Atmospheric Rivers and Tropical Cyclones
Ludewigs, Leon, 2021: Detection and 3D Visualization of Atmospheric Polar Vortices in Numerical Weather Prediction
Sander, Dominik, 2021: Informationsvisualisierung zur Analyse von Ähnlichkeiten in Ensemble-Wettervorhersagen
Panten, Jessica, 2021: Segmentation of numerical weather prediction data for
characterization of atmospheric airmasse
Kaufhold, Christine, 2022: xAI Techniques for Ensemble Uncertainty Analysis: Determining Structures of Relevance for Weather Forecasting.
Rolff, Tim, 2020: Segmentation of Noisy Volume Data. [Publication]
Liu, Zhichang, 2019: Cluster-based visualization of uncertainty in ensemble weather predictions.
Hellmich, Lara, 2019: The Northern Hemisphere Winter Polar Jet Stream and ist connection to seasonal prediction skill of weather patterns over Europe.