Claire Kenyon-Mathieu

9 papers receiving 183 citations

Peers

Claire Kenyon-Mathieu
Comparison fields: 5 of 42
  • Computational Theory and Mathematics 98
  • Computer Networks and Communications 72
  • Artificial Intelligence 65
  • Management Science and Operations Research 59
  • Economics and Econometrics 49
Replace Christine T. Cheng with:
Christine T. Cheng United States
Warren Schudy United States
Naonori Kakimura Japan
Sebastian Ordyniak Austria
Ami Paz Israel
Henrik Björklund Sweden
Johannes Uhlmann Germany
Joost P. Warners Netherlands
Christoph Ambühl Switzerland
A. V. Karzanov Russia
Claire Kenyon-Mathieu relative to Christine T. Cheng United States Christine T. Cheng's profile →
Citations per field
00.5×2.8×
Christine T. Cheng · 1×
Citations per year

Countries citing papers authored by Claire Kenyon-Mathieu

Since Specialization
Citations

This map shows the geographic impact of Claire Kenyon-Mathieu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Claire Kenyon-Mathieu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claire Kenyon-Mathieu more than expected).

Fields of papers citing papers by Claire Kenyon-Mathieu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Claire Kenyon-Mathieu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Claire Kenyon-Mathieu. The network helps show where Claire Kenyon-Mathieu may publish in the future.

Co-authorship network of co-authors of Claire Kenyon-Mathieu

This figure shows the co-authorship network connecting the top 25 collaborators of Claire Kenyon-Mathieu. A scholar is included among the top collaborators of Claire Kenyon-Mathieu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Claire Kenyon-Mathieu. Claire Kenyon-Mathieu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 2
2 17
3 32
4 106
5
How to rank with few errors: A PTAS for Weighted Feedback Arc Set on Tournaments.
12
6 17
7 4
8 5
9
General Methods for the Analysis of the Maximum Size of Data Structures
1

About Claire Kenyon-Mathieu

Claire Kenyon-Mathieu is a scholar working on Management Science and Operations Research, Industrial and Manufacturing Engineering and Computer Networks and Communications, having authored 9 papers that have together received 196 indexed citations. Recurring topics across this work include Optimization and Search Problems (4 papers), Algorithms and Data Compression (3 papers) and Game Theory and Voting Systems (2 papers). The work is most often cited by research in Computational Theory and Mathematics (98 citations), Management Science and Operations Research (59 citations) and Computer Networks and Communications (72 citations). Claire Kenyon-Mathieu has collaborated with scholars based in United States and Canada. Frequent co-authors include Warren Schudy, Marek Chrobák, Irit Katriel, Eli Upfal, Jeffrey Scott Vitter, Valerie King and Aparna Das. Their work appears in journals such as SIAM Journal on Computing, Theoretical Computer Science and Theory of Computing Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026