H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 33 Citations 5,264 163 World Ranking 6646 National Ranking 319
Mathematics H-index 30 Citations 4,226 119 World Ranking 2109 National Ranking 136

Overview

What is she best known for?

The fields of study she is best known for:

  • Algorithm
  • Artificial intelligence
  • Combinatorics

Her primary areas of study are Combinatorics, Discrete mathematics, Time complexity, Graph and Algorithm. Planar graph, Vertex, Steiner tree problem, Book embedding and Subgraph isomorphism problem are among the areas of Combinatorics where Petra Mutzel concentrates her study. Her studies deal with areas such as Embedding and Graph as well as Discrete mathematics.

Her Time complexity research focuses on subjects like Planarity testing, which are linked to Monotone polygon, Directed acyclic graph, Software, Unified Modeling Language and Class diagram. Her Graph study combines topics in areas such as Graph theory and Approximation algorithm. Petra Mutzel works mostly in the field of Algorithm, limiting it down to topics relating to Mathematical optimization and, in certain cases, Polytope.

Her most cited work include:

  • Graph Drawing Software (299 citations)
  • A Linear Time Implementation of SPQR-Trees (207 citations)
  • An Algorithmic Framework for the Exact Solution of the Prize-Collecting Steiner Tree Problem (179 citations)

What are the main themes of her work throughout her whole career to date?

Petra Mutzel mainly investigates Combinatorics, Discrete mathematics, Algorithm, Planar graph and Graph. Her research on Combinatorics often connects related topics like Planar. Her study in Algorithm is interdisciplinary in nature, drawing from both Heuristics, Integer and Minification.

The concepts of her Planar graph study are interwoven with issues in Planarity testing, Embedding, Set, Graph drawing and Edge. Her research integrates issues of Graph and Engineering drawing in her study of Graph drawing. As part of one scientific family, Petra Mutzel deals mainly with the area of Graph, narrowing it down to issues related to the Theoretical computer science, and often Visualization.

She most often published in these fields:

  • Combinatorics (39.57%)
  • Discrete mathematics (29.50%)
  • Algorithm (23.02%)

What were the highlights of her more recent work (between 2015-2021)?

  • Graph (20.86%)
  • Algorithm (23.02%)
  • Combinatorics (39.57%)

In recent papers she was focusing on the following fields of study:

Petra Mutzel mainly focuses on Graph, Algorithm, Combinatorics, Time complexity and Crossing number. Her Graph research incorporates elements of Theoretical computer science and Computation. The study incorporates disciplines such as Contrast, Shortest path problem, Triangle inequality and Metric in addition to Algorithm.

Her Combinatorics research focuses on Discrete mathematics and how it relates to Integer programming. Her Time complexity research incorporates themes from PSPACE, Bounded function, Degree and Vertex. Her research integrates issues of Pathwidth, Treewidth and Conjecture in her study of Crossing number.

Between 2015 and 2021, her most popular works were:

  • Faster Kernels for Graphs with Continuous Attributes via Hashing (41 citations)
  • Glocalized Weisfeiler-Lehman Graph Kernels: Global-Local Feature Maps of Graphs (37 citations)
  • TUDataset: A collection of benchmark datasets for learning with graphs. (36 citations)

In her most recent research, the most cited papers focused on:

  • Algorithm
  • Artificial intelligence
  • Programming language

Petra Mutzel spends much of her time researching Graph, Algorithm, Computation, Theoretical computer science and Time complexity. Her work on Crossing number, Maximum cut, Vertex and Graph classification as part of general Graph research is frequently linked to Kernel, bridging the gap between disciplines. Her Algorithm research includes elements of Dependency, Helix and Set.

Her study explores the link between Computation and topics such as Graph that cross with problems in Polytope and Branch and cut. Her Time complexity study is associated with Combinatorics. Her research brings together the fields of Discrete mathematics and Combinatorics.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Graph Drawing Software

Michael Junger;Petra Mutzel.
(2003)

299 Citations

A Linear Time Implementation of SPQR-Trees

Carsten Gutwenger;Petra Mutzel.
graph drawing (2000)

289 Citations

2-Layer Straightline Crossing Minimization: Performance of Exact and Heuristic Algorithms

Michael Jünger;Petra Mutzel.
Journal of Graph Algorithms and Applications (1997)

264 Citations

An Algorithmic Framework for the Exact Solution of the Prize-Collecting Steiner Tree Problem

Ivana Ljubić;René Weiskircher;Ulrich Pferschy;Gunnar W. Klau.
Mathematical Programming (2006)

262 Citations

Interactive exploration of chemical space with Scaffold Hunter.

Stefan Wetzel;Karsten Klein;Steffen Renner;Daniel Rauh.
Nature Chemical Biology (2009)

230 Citations

A graph–theoretic approach to steganography

Stefan Hetzl;Petra Mutzel.
international conference on communications (2005)

191 Citations

Exact Ground States of Ising Spin Glasses: New Experimental Results With a Branch and Cut Algorithm

C. De Simone;M. Diehl;M. Jünger;P. Mutzel.
Journal of Statistical Physics (1995)

179 Citations

The Open Graph Drawing Framework (OGDF)

Markus Chimani;Carsten Gutwenger;Michael Jünger;Gunnar W. Klau.
graph drawing (2012)

143 Citations

On the embedding phase of the Hopcroft and Tarjan planarity testing algorithm

Kurt Mehlhorn;Petra Mutzel.
Algorithmica (1996)

133 Citations

Maximum planar subgraphs and nice embeddings: Practical layout tools

Michael Jünger;Petra Mutzel.
Algorithmica (1996)

131 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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