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Computer Science I - Computational Analytics

Research Interests

  • 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, …

Current Research Topics

  • 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.

Recent Publications

start.txt · Last modified: 2020/11/08 19:30 by petra.mutzel

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