Contact

Fabian Klute
Institute of Logic and Computation
TU Wien
Favoritenstraße 9–11, E192-01
1040 Vienna
Austria
Room: HA0416
Phone: +43(1)58801–192133
E-mail: fklute (at) ac.tuwien.ac.at
Welcome! I am Fabian Klute, currently I am a PhD student in the Algorithm and Complexity Group at TU Wien. I come from Landau/Palatina in Germany and studied my Bachelor's and Master's degree in Karlsruhe.

My main research interests are in the area of graph drawing. At the moment I am very interested in circular layouts and confluent drawings, as well as parametrized complexity and its application to graph drawing.
Short CV:
April 2016 – Present
PhD Student in the Algorithms and Complexity Group at TU Wien under the supervision of Prof. Martin Nöllenburg
May 2015 – December 2015
Gap months, some impressions can be found here
April 2013 – April 2015
Master of Science at the Karlsruher Institute of Technology (KIT)
October 2009 – March 2013
Bachelor of Science at the Karlsruher Institute of Technology (KIT)

I enjoy a lot to participate in the yearly contest held at the Graph Drawing conference. Over the years I created several posters.

GD'18 – 4th place

Submission for the GD Contest 2018 together with Carlos Hidalgo-Toscano and Irene Parada. The presented data is a graph based on Game of Thrones.

GD'17 – 1st place

Submission for the GD Contest 2017 together with Irene Parada. The data is taken from the human metabolism project. In order to filter the information, we thin out the graph in a preprocessing step. For every reaction we keep only the lowest-degree reactant and product. Isolated and degree one nodes are removed and only the biggest component is kept. Additionally we identify nodes corresponding to different biological compartments (e.g. co2[c], co2[e] are contracted into one co2 node).
To generate the layout we add edges to keep the subsystems closer together. The size of the nodes depends on its betweenes in the reduced graph. Then the layout is calculated using the Fruchterman-Reingold algorithm. Finally we color the nodes based on subsystems. We distinguish two big groups of subsystems, the communication or transportation ones and the proper ones. As the name suggests the first kind mainly connects the proper subsystems. Based on this we categorize nodes into five cases, depending on if they are inside a proper subsystem, on its boundary, in a transport system, on the boundary between two different transport systems, or between two proper subsystems.

GD'16 – 1st place

Submission for the GD Contest 2016. The data is an experpt of the data surfaced in the panama papers. Graph and layout were produced by exploring the graph with yed, R, whatever C program I had lying around. I focused mainly on finding sets of strongly connected vertices. I noticed a group of eleven vertices which are connected by an undirected circle and on top are almost all connected to each other in some way. I extracted this group and made one visualization for them in Ipe (left half). Among the leftover vertices a lot of them have no incoming edges so I plotted them in treemaps using R. These treemaps I then used as vertices and connected them with the other remaining vertices with incoming edges that were not part of the above mentioned group (right half). All layouting was done in Ipe by hand with the help of a couple of python scripts generating e.g. the legend.
SS19
Algorithmen und Datenstrukturen. Exercise lessons. Redesign of the programming part of the course. [Link]
Graph Drawing Algorithms. Exercise lessons and coordination. [Link]
WS18/19
Algorithmic Geometry. Exercise lessons and designing the exercise sheets. [Link]
Seminar in Algorithms Graphs and Geometry. [Link]
SS18
Algorithmen und Datenstrukturen. Exercise lessons and programming exercises. [Link]
Graph Drawing Algorithms. Exercise lessons and coordination. [Link]
WS17/18
Algorithmic Geometry. Exercise lessons and designing the exercise sheets. [Link]
Heuristic Optimization Techniques. Help with exercises. [Link]
Seminar in Algorithms Graphs and Geometry. [Link]
SS17
Algorithmen und Datenstrukturen. Exercise lessons. [Link]
Seminar in Algorithms. [Link]
WS16/17
Algorithmic Geometry. Exercise lessons and designing the exercise sheets. [Link]
Seminar in Algorithms. [Link]
SS16
Algorithmen und Datenstrukturen. Exercise lessons. [Link]

    Articles in conferences and workshops

  • Efficient Segment Folding Is Hard.
    T. Horiyama, F. Klute, M. Korman, I. Parada, R. Uehara, and K. Yamanaka
    31st Canadian Conference in Computational Geometry (CCCG'19), 2019.
  • Exploring Semi-Automatic Map Labeling.
    F. Klute, G. Li, R. Löffler, M. Nöllenburg, and M. Schmidt
    27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL'19), 2019.
  • Extending to 1-Plane Drawings.
    T. Hamm, F. Klute, and I. Parada
    Abstracts of the XVIII Spanish Meeting on Computational Geometry (EGC'19), 30–33, 2019.
  • Maximizing Ink in Partial Edge Drawings of K-Plane Graphs.
    M. Hummel, F. Klute, S. Nickel, and M. Nöllenburg
    Graph Drawing and Network Visualization (GD'19), 2019.
    Maximizing Ink in Symmetric Partial Edge Drawings of K-Plane Graphs.
    M. Höller, F. Klute, S. Nickel, M. Nöllenburg, and B. Schreiber
    34th European Workshop on Computational Geometry (EuroCG'18), 50:1-50:6, 2018.
  • Mixed Linear Layouts: Complexity, Heuristics, and Experiments.
    P. de Col, F. Klute, and M. Nöllenburg
    Graph Drawing and Network Visualization (GD'19), 2019.
  • On Strict (Outer-)Confluent Graphs.
    H. Förster, R. Ganian, F. Klute, and M. Nöllenburg
    Graph Drawing and Network Visualization (GD'19), 2019.
  • Minimizing Crossings in Constrained Two-Sided Circular Graph Layouts.
    F. Klute and M. Nöllenburg
    34th International Symposium on Computational Geometry (SoCG'18), volume 99 of Leibniz International Proceedings in Informatics (LIPIcs), 53:1–53:14, 2018.
    Minimizing Crossings in Constrained Two-Sided Circular Graph Layouts.
    F. Klute and M. Nöllenburg
    33rd European Workshop on Computational Geometry (EuroCG'17), 273-276, 2017.
  • On Structural Parameterizations of the Bounded-Degree Vertex Deletion Problem.
    R. Ganian, F. Klute, and S. Ordyniak
    35th Symposium on Theoretical Aspects of Computer Science (STACS'18), volume 96 of Leibniz International Proceedings in Informatics (LIPIcs), 33:1–33:14, 2018.
  • Scientific poster

  • Towards Characterizing Strict Outerconfluent Graphs.
    F. Klute and M. Nöllenburg
    Graph Drawing and Network Visualization (GD'17), volume 10692 of LNCS, 612–614, 2018.
  • Robust Genealogy Drawings.
    F. Klute
    Graph Drawing and Network Visualization (GD'16), volume 9801 of LNCS, 637-639, 2016.
  • PiGra – a Tool for Pixelated Graph Representations.
    T. Bläsius, F. Klute, B. Niedermann, and M. Nöllenburg
    Graph Drawing (GD'14), volume 8871 of LNCS, 513–514, 2014.
  • Theses

  • Connecting Points with Low-Complexity Polynomial Curves in a Polygon.
    F. Klute
    Master's Thesis, {Karlsruhe Institute of Technology (KIT)}, 2015.
  • Serealisierung Und Deserialisierung von Mustern in Zellularautomaten.
    F. Klute
    Bachelor's Thesis, {Karlsruhe Institute of Technology (KIT)}, 2012.