Dan Gordon

47 papers receiving 1.2k citations

Peers

Dan Gordon
Comparison fields: 5 of 93
  • Computer Graphics and Computer-Aided Design 343
  • Numerical Analysis 149
  • Structural Biology 38
  • Computational Mechanics 512
  • Computer Vision and Pattern Recognition 399
Replace Jean–François Aujol with:
Jean–François Aujol France
Y.Y. Zeevi Israel
Nicolas Boumal United States
Afonso S. Bandeira United States
Don P. Mitchell United States
M. Ibrahim Sezan United States
Yen‐Hsi Richard Tsai United States
Fernando de Goes United States
Leonid Yaroslavsky Israel
J. Biemond Netherlands
Dan Gordon relative to Jean–François Aujol France Jean–François Aujol's profile →
Citations per field
00.5×3.5×
Jean–François Aujol · 1×
Citations per year

Countries citing papers authored by Dan Gordon

Since Specialization
Citations

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

Fields of papers citing papers by Dan Gordon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Dan Gordon, 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 Dan Gordon Line = papers co-authored together Dan Gordon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001149
2 1983143
3 1985134
4 2012107
5 198591
6 198979
7 198473
8 200164
9 200560
10 198752
11 199531
12 201030
13 198527
14 198727
15 199126
16 198426
17 200825
18 201224
19 199820
20 201518

About Dan Gordon

Dan Gordon is a scholar working on Computational Mechanics, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Electrical and Electronic Engineering, having authored 47 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Numerical Methods in Computational Mathematics (11 papers), Computer Graphics and Visualization Techniques (11 papers), Electromagnetic Scattering and Analysis (8 papers), Matrix Theory and Algorithms (8 papers), Electromagnetic Simulation and Numerical Methods (7 papers), Medical Imaging Techniques and Applications (6 papers), Digital Image Processing Techniques (5 papers) and Computational Geometry and Mesh Generation (5 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (343 citations), Numerical Analysis (149 citations), Structural Biology (38 citations), Computational Mechanics (512 citations) and Computer Vision and Pattern Recognition (399 citations). Dan Gordon has collaborated with scholars based in Israel, United States and Spain. Frequent co-authors include Rachel Gordon, Roger Reynolds, Yair Censor, P. P. B. Eggermont, Gideon Frieder, Jayaram K. Udupa, Stanley Waterman, Eli Turkel, Semyon Tsynkov and Yosi Ben-Asher. Their work appears in journals such as IEEE Computer Graphics and Applications, IEEE Transactions on Computers, Parallel Computing, Journal of Parallel and Distributed Computing and Journal of Computational and Applied Mathematics.

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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