Algorithmic Data Analytics for Geodesy
The goal of our Research Unit AlgoForGe (DFG KI-FOR 5361) is to study the algorithmic challenges of fundamental AI problems in geodesy
and develop data analysis methods and tools. The RU has been selected in July 2022 as one of eight new AI research units
by the German Research Foundation (DFG).
Approach and Concept
- represent input data geometrically
- focus on unsupervised learning
- state as discrete optimization problem
Key Tasks
- Dealing with geometric objects (points, lines, polygons, trajectories, triangulations, geometric graphs)
- Solving the tasks: Aggregation, Simplification, Clustering
Our Team
Our interdisciplinary team consists of members of the University of Bonn, the University of Cologne, and the University of Duesseldorf
from the areas of computer science, cartography, and geodesy.
We have expertise in, e.g., algorithm engineering, approximation algorithms, cartography, clustering, core sets,
Fréchet distance, GIS, graph optimization,
interactive maps, multi-objective optimization, smoothed analysis, sea level geodesy, streaming, sublinear algorithms, and
triangulations.
Anne Driemel
Computational Geometry
Jan-Henrik Haunert
Geoinformation
Jürgen Kusche
Geodesy and Sea Level
Petra Mutzel
Computational Analytics
Heiko Röglin
Theoretical Computer Science
Melanie Schmidt
Geometric Data Analysis
Christian Sohler
Algorithmic Data Analysis