Gerik Scheuermann

191 papers receiving 2.8k citations

Peers

Gerik Scheuermann
Comparison fields: 5 of 148
  • Computer Graphics and Computer-Aided Design 1.0k
  • Computational Mathematics 59
  • Computer Vision and Pattern Recognition 1.5k
  • Signal Processing 303
  • Computational Theory and Mathematics 444
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Countries citing papers authored by Gerik Scheuermann

Since Specialization
Citations

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

Fields of papers citing papers by Gerik Scheuermann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gerik Scheuermann, 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 Gerik Scheuermann Line = papers co-authored together Gerik Scheuermann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 201 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009174
2 2015137
3 200187
4 201685
5 201677
6 199873
7 200271
8 200667
9 200162
10 200560
11
The State of the Art in Flow Visualization: Partition-Based Techniques
200855
12 200554
13 200852
14 200852
15 200851
16 200451
17 200250
18 201047
19 201246
20 201140

About Gerik Scheuermann

Gerik Scheuermann is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Artificial Intelligence, Computational Mechanics and Computational Theory and Mathematics, having authored 201 papers that have together received 3.0k indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (67 papers), Data Visualization and Analytics (54 papers), Advanced Vision and Imaging (21 papers), Advanced Neuroimaging Techniques and Applications (21 papers), Topological and Geometric Data Analysis (18 papers), Fluid Dynamics and Turbulent Flows (15 papers), Advanced Numerical Analysis Techniques (12 papers) and Computational Physics and Python Applications (11 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (1.0k citations), Computational Mathematics (59 citations), Computer Vision and Pattern Recognition (1.5k citations), Signal Processing (303 citations) and Computational Theory and Mathematics (444 citations). Gerik Scheuermann has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Xavier Tricoche, Thomas Wischgoll, H. Jänicke, Stefan Jänicke, Hans Hagen, Christoph Garth, Alexander Wiebel, Greta Franzini, Muhammad Faisal Cheema and Hans Hagen. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, IEEE Computer Graphics and Applications, The Visual Computer and NeuroImage.

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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