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- Algorithm Engineering for big data, in particular graph algorithms and data structures
- Algorithmic Data Analysis, Graph Mining
- Combinatorial Optimization (polynomial time and ILP-based)
- Network Design and Optimization
- Graph and Network Visualization
- Analysis of chemical structures and biological networks
- Application areas: network analysis, cheminformatics (drug design), information visualization, network design and optimization, computational biology, statistical physics, …

- Temporal graphs, e.g., bicriteria shortest paths, temporal TSP
- Graph Learning, e.g., Weisfeiler-Leman type algorithms
- Combining combinatorial optimization and learning methods, e.g. Max Cut and TSP
- Algorithms for almost planar graphs, e.g., Max Cut
- Cheminformatics, e.g. structural clustering, Scaffold Hunter
- Integer Linear Programming Models for ranking problems, e.g. graph coloring, Steiner tree with hop constraints, layering problem in graph drawing
- High Performance Analytics

Our current and past projects can be found here.

start.txt · Last modified: 2020/03/26 17:21 by jonas.charfreitag