ags:coan

- 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
- graph similarity, graph mining
- 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.

Our recent publications can be found here.

ags/coan.txt · Last modified: 2022/05/04 15:07 by petra.mutzel