World's Best Scientists 2026 revealed!
Soshi Kawai

Soshi Kawai

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
31
Citations
4437
World Ranking
3281
National Ranking
76

Soshi Kawai publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Soshi Kawai sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 181 publications — 37th percentile

37% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Soshi Kawai D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Soshi Kawai sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 31 D-Index — 6th percentile

6% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Best Publications

  • Wall-modeling in large eddy simulation: Length scales, grid resolution, and accuracy

    Soshi Kawai;Johan Larsson

  • Large eddy simulation with modeled wall-stress: recent progress and future directions

    Johan Larsson;Soshi Kawai;Julien Bodart;Ivan Bermejo-Moreno

  • Large-Eddy Simulation of Jet Mixing in Supersonic Crossflows

    Soshi Kawai;Soshi Kawai;Sanjiva K. Lele

  • Assessment of localized artificial diffusivity scheme for large-eddy simulation of compressible turbulent flows

    Soshi Kawai;Santhosh K. Shankar;Sanjiva K. Lele

  • Localized artificial diffusivity scheme for discontinuity capturing on curvilinear meshes

    S. Kawai;S. K. Lele

  • Dynamic non-equilibrium wall-modeling for large eddy simulation at high Reynolds numbers

    Soshi Kawai;Johan Larsson

  • Improving Low-Frequency Characteristics of Recycling/Rescaling Inflow Turbulence Generation

    Brandon Morgan;Johan Larsson;Soshi Kawai;Sanjiva K. Lele

  • Kinetic energy and entropy preserving schemes for compressible flows by split convective forms

    Unknown

  • Two-dimensional viscous flow simulation of a shock accelerated heavy gas cylinder

    Santhosh K. Shankar;Soshi Kawai;Sanjiva K. Lele

  • Computational Study of a Supersonic Base Flow Using Hybrid Turbulence Methodology

    Soshi Kawai;Soshi Kawai;Kozo Fujii

  • Compact Scheme with Filtering for Large-Eddy Simulation of Transitional Boundary Layer

    Soshi Kawai;Soshi Kawai;Kozo Fujii

  • Large-eddy simulation of airfoil flow near stall condition at Reynolds number 2.1 × 106

    Unknown

  • Heated transcritical and unheated non-transcritical turbulent boundary layers at supercritical pressures

    Unknown

  • A robust and accurate numerical method for transcritical turbulent flows at supercritical pressure with an arbitrary equation of state

    Unknown

  • High-Resolution Numerical Method for Supercritical Flows with Large Density Variations

    Hiroshi Terashima;Hiroshi Terashima;Soshi Kawai;Soshi Kawai;Nobuhiro Yamanishi

  • Mechanisms of surface pressure distribution within a laminar separation bubble at different Reynolds numbers

    Donghwi Lee;Soshi Kawai;Taku Nonomura;Masayuki Anyoji

  • A high‐resolution scheme for compressible multicomponent flows with shock waves

    Soshi Kawai;Hiroshi Terashima

  • Mechanisms of Jet Mixing in a Supersonic Crossflow: A Study Using Large-Eddy Simulation

    Soshi Kawai;Sanjiva K. Lele

  • Wall-modeled large-eddy simulation of high Reynolds number flow around an airfoil near stall condition

    Unknown

  • High-order accurate kinetic-energy and entropy preserving (KEEP) schemes on curvilinear grids

    Yuichi Kuya;Soshi Kawai

Frequent Co-Authors

Kozo Fujii
Kozo Fujii Tokyo University of Science
Sanjiva K. Lele
Sanjiva K. Lele Stanford University
Taku Nonomura
Taku Nonomura Nagoya University
Johan Larsson
Johan Larsson University of Maryland, College Park
Kazuhiro Nakahashi
Kazuhiro Nakahashi Tohoku University
Juan J. Alonso
Juan J. Alonso Stanford University

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Related Online Degrees & Career Pathways

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