M. Koishi

750 citations
18 papers · 588 indexed · 1 hit paper · h-index 11

M. Koishi

18 papers receiving 534 citations

Hit Papers

A deep material network for multiscale topology learning ...234201820262020202350100150200

Peers

M. Koishi
Comparison fields: 5 of 52
  • Mechanics of Materials 323
  • Civil and Structural Engineering 173
  • Automotive Engineering 88
  • Mechanical Engineering 202
  • Statistical and Nonlinear Physics 65
Replace Q. S. Nguyen with:
Q. S. Nguyen France
A. Poitou France
A. de Kraker Netherlands
Karl A. Kalina Germany
Hang Yang China
Jean‐Luc Dion France
Wing K. Liu United States
Zhe Ding China
Pierre Beauchêne France
Erman Guleryuz United States
M. Koishi relative to Q. S. Nguyen France Q. S. Nguyen's profile →
Citations per field
00.5×1.5×2.4×
Q. S. Nguyen · 1×
Citations per year

Countries citing papers authored by M. Koishi

Since Specialization
Citations

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

Fields of papers citing papers by M. Koishi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 12 scholars most cited alongside M. Koishi, 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 M. Koishi Line = papers co-authored together M. Koishi links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 201946
2 201910
3
A deep material network for multiscale topology learning and accelerated nonlinear modeling of heterogeneous materialsbreakdown →
2018234
4 20183
5 20163
6 201544
7 20157
8 201423
9 201234
10 20119
11 200919
12 20067
13 20069
14 200114
15 200132
16 199954
17 199833
18 19927

About M. Koishi

M. Koishi is a scholar working on Mechanics of Materials, Computational Mechanics and Civil and Structural Engineering, having authored 18 papers that have together received 588 indexed citations. Recurring topics across this work include Mechanical Engineering and Vibrations Research (7 papers), Numerical methods in engineering (6 papers), Elasticity and Material Modeling (4 papers), Advanced Numerical Methods in Computational Mathematics (4 papers), Composite Material Mechanics (3 papers), Soil Mechanics and Vehicle Dynamics (2 papers), Engineering Applied Research (2 papers) and Electromagnetic Simulation and Numerical Methods (2 papers). The work is most often cited by research in Mechanics of Materials (323 citations), Civil and Structural Engineering (173 citations) and Automotive Engineering (88 citations). M. Koishi has collaborated with scholars based in Japan and United States. Frequent co-authors include Zeliang Liu, Cheng Wu, C.T. Wu, Wei Hu, M. Shiratori, Sanjay Govindjee, Junichiro Yamabe, Yuji Kodama, Youcai Wu and Takashi Kojima. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, International Journal for Numerical Methods in Engineering and Computational Mechanics.

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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