Atsushi Katsuda

466 citations
20 papers · 224 indexed · h-index 6
Topics
Geometric Analysis and Curvature Flows (9 papers)Advanced Mathematical Modeling in Engineering (5 papers)Numerical methods in inverse problems (5 papers)

In The Last Decade

Atsushi Katsuda

18 papers receiving 168 citations

Peers

Atsushi Katsuda
Comparison fields: 5 of 31
  • Mathematical Physics 144
  • Geometry and Topology 113
  • Applied Mathematics 107
  • Computational Theory and Mathematics 65
  • Statistical and Nonlinear Physics 32
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Bun Wong United States
Lavi Karp Israel
Bruno Colbois Switzerland
Kenrô Furutani Japan
Steen Markvorsen Denmark
Chaofeng Zhu China
Yuri A. Kordyukov Russia
Carlo Morpurgo United States
Masahiko Kanai Japan
Craig A. Nolder United States
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Countries citing papers authored by Atsushi Katsuda

Since Specialization
Citations

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

Fields of papers citing papers by Atsushi Katsuda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Atsushi Katsuda

This figure shows the co-authorship network connecting the top 25 collaborators of Atsushi Katsuda. A scholar is included among the top collaborators of Atsushi Katsuda 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 Atsushi Katsuda. Atsushi Katsuda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 1
3 0
4 8
5 59
6
Stability and reconstruction in Gelfand inverse boundary spectral problem
1
7 2
8
BC-method and Stability of Gel'fand inverse spectral problem (Spectral and Scattering Theory and Related Topics)
1
9 11
10 3
11 42
12 4
13 1
14 2
15 1
16 35
17 4
18 2
19 3
20 42

About Atsushi Katsuda

Atsushi Katsuda is a scholar working on Geometry and Topology, Mathematical Physics and Applied Mathematics, having authored 20 papers that have together received 224 indexed citations. Recurring topics across this work include Geometric Analysis and Curvature Flows (9 papers), Advanced Mathematical Modeling in Engineering (5 papers) and Numerical methods in inverse problems (5 papers). The work is most often cited by research in Mathematical Physics (144 citations), Geometry and Topology (113 citations) and Applied Mathematics (107 citations). Atsushi Katsuda has collaborated with scholars based in Japan, United Kingdom and Finland. Frequent co-authors include Toshikazu Sunada, Matti Lassas, Yaroslav Kurylev, Michael G. Taylor, Michael T. Anderson, Hironobu Fujii, Hajime Urakawa, Yoshiyuki Naito, Takeshi Kobayashi and Michael E. Taylor. Their work appears in journals such as Inventiones mathematicae, Bulletin of the American Mathematical Society and American Journal of 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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