Masahisa Tabata

68 total papers · 809 total citations
32 papers, 509 citations indexed

About

Masahisa Tabata is a scholar working on Computational Mechanics, Numerical Analysis and Computational Theory and Mathematics. According to data from OpenAlex, Masahisa Tabata has authored 32 papers receiving a total of 509 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computational Mechanics, 15 papers in Numerical Analysis and 8 papers in Computational Theory and Mathematics. Recurrent topics in Masahisa Tabata's work include Advanced Numerical Methods in Computational Mathematics (27 papers), Computational Fluid Dynamics and Aerodynamics (12 papers) and Differential Equations and Numerical Methods (11 papers). Masahisa Tabata is often cited by papers focused on Advanced Numerical Methods in Computational Mathematics (27 papers), Computational Fluid Dynamics and Aerodynamics (12 papers) and Differential Equations and Numerical Methods (11 papers). Masahisa Tabata collaborates with scholars based in Japan, China and Germany. Masahisa Tabata's co-authors include Hongxing Rui, Hirofumi Notsu, Mária Lukáčová–Medvid’ová, Atsushi Suzuki, Yoshiichi Ozeki and Satoru Honda and has published in prestigious journals such as SHILAP Revista de lepidopterología, Mathematics of Computation and International Journal for Numerical Methods in Engineering.

In The Last Decade

Masahisa Tabata

32 papers receiving 470 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Masahisa Tabata	439	198	124	84	71	32	509
Ram P. Manohar	429 1.0×	222 1.1×	74 0.6×	56 0.7×	14 0.2×	21	523
Eleanor W. Jenkins	389 0.9×	82 0.4×	162 1.3×	95 1.1×	28 0.4×	36	517
Haibiao Zheng	517 1.2×	106 0.5×	268 2.2×	161 1.9×	14 0.2×	39	573
Andrea Bonito	352 0.8×	63 0.3×	154 1.2×	151 1.8×	23 0.3×	36	497
Roger Pierre	497 1.1×	56 0.3×	111 0.9×	115 1.4×	137 1.9×	28	607
Fatih Celiker	322 0.7×	165 0.8×	93 0.8×	169 2.0×	7 0.1×	31	482
Neela Nataraj	393 0.9×	140 0.7×	156 1.3×	228 2.7×	9 0.1×	63	465
Piotr Skrzypacz	208 0.5×	121 0.6×	109 0.9×	105 1.3×	8 0.1×	45	515
Jean‐Pierre Croisille	407 0.9×	120 0.6×	101 0.8×	80 1.0×	4 0.1×	37	508
J.‐C. Latché	477 1.1×	50 0.3×	83 0.7×	15 0.2×	94 1.3×	28	534

Countries citing papers authored by Masahisa Tabata

Since Specialization

Citations

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

Fields of papers citing papers by Masahisa Tabata

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masahisa Tabata

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

All Works

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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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