Michael Kaufmann

155 papers receiving 2.1k citations

Peers

Michael Kaufmann
Comparison fields: 5 of 179
  • Computer Graphics and Computer-Aided Design 448
  • Computer Vision and Pattern Recognition 498
  • Computational Theory and Mathematics 330
  • Signal Processing 158
  • Software 49
Replace Carlos Scheidegger with:
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Reinhard Diestel Germany
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Michael Kaufmann relative to Carlos Scheidegger United States Carlos Scheidegger's profile →
Citations per field
00.5×3.8×
Carlos Scheidegger · 1×
Citations per year

Countries citing papers authored by Michael Kaufmann

Since Specialization
Citations

This map shows the geographic impact of Michael Kaufmann'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 Michael Kaufmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Kaufmann more than expected).

Fields of papers citing papers by Michael Kaufmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Kaufmann. 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 Michael Kaufmann. The network helps show where Michael Kaufmann may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael Kaufmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Kaufmann Line = papers co-authored together Michael Kaufmann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 173 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011206
2 2001177
3 2008172
4 2005112
5 2016110
6 200870
7 201167
8 199965
9 200561
10 200657
11 199651
12 198447
13 200242
14 200241
15 200241
16 199439
17 200938
18 200336
19 201231
20 200431

About Michael Kaufmann

Michael Kaufmann is a scholar working on Computer Graphics and Computer-Aided Design, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 173 papers that have together received 2.3k indexed citations. Recurring topics across this work include Computational Geometry and Mesh Generation (75 papers), Advanced Graph Theory Research (43 papers), Data Visualization and Analytics (23 papers), Digital Image Processing Techniques (20 papers), VLSI and FPGA Design Techniques (17 papers), Interconnection Networks and Systems (17 papers), Data Management and Algorithms (16 papers) and Complexity and Algorithms in Graphs (12 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (448 citations), Computer Vision and Pattern Recognition (498 citations), Computational Theory and Mathematics (330 citations), Signal Processing (158 citations) and Software (49 citations). Michael Kaufmann has collaborated with scholars based in Germany, United States and Italy. Frequent co-authors include Burkhard Morgenstern, Andreas Gerasch, Hans‐Peter Lenhof, Christina Backes, Michael A. Bekos, Antonios Symvonis, Andreas Keller, Katharina A. Zweig, Peter Nicholls and Eckart Meese. Their work appears in journals such as Journal of Graph Algorithms and Applications, Algorithmica, Computational Geometry, Theoretical Computer Science and BMC Bioinformatics.

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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