• Computational Analytics
• 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.