World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
57
Citations
11841
World Ranking
696
National Ranking
350

Engineering and Technology

D-Index
57
Citations
11909
World Ranking
2655
National Ranking
812

Mikhail Shashkov publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Mikhail Shashkov sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 181 publications — 54th percentile

54% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Mikhail Shashkov D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Mikhail Shashkov sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 57 D-Index — 82nd percentile

82% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Research.com Recognitions

  • 2014 - SIAM Fellow For contributions to the development of mimetic finite difference methods for nonlinear systems of partial differential equations.

Overview

Mikhail Shashkov is affiliated with Los Alamos National Laboratory in the United States. Their research primarily spans the fields of Engineering and Computer Science, with substantial contributions in Computational Mechanics. Their work intersects multiple subfields including Computer Graphics and Computer-Aided Design, Nuclear and High Energy Physics, Computer Networks and Communications, and Surfaces, Coatings and Films.

The focal topics of Shashkov's research include Fluid Dynamics and Heat Transfer, Computational Fluid Dynamics and Aerodynamics, Computer Graphics and Visualization Techniques, Advanced Numerical Methods in Computational Mathematics, Fluid Dynamics Simulations and Interactions, Laser-Plasma Interactions and Diagnostics, and Advanced Data Storage Technologies.

Shashkov has published extensively, with a strong presence in high-impact journals such as the Journal of Computational Physics, Computers & Fluids, and Communications on Applied Mathematics and Computation. Frequent appearances in the SSRN Electronic Journal also form part of their publication record.

Recent notable papers authored by Shashkov are:

  • Moments-based interface reconstruction, remap and advection, 2023, Journal of Computational Physics
  • An adaptive moments-based interface reconstruction using intersection of the cell with one half-plane, two half-planes and a circle, 2023, Journal of Computational Physics

Other key papers relevant to their research area, though with different lead authors, include:

  • A reconstructed discontinuous Galerkin method for compressible flows in Lagrangian formulation, 2020, Computers & Fluids
  • Locally adaptive artificial viscosity strategies for Lagrangian hydrodynamics, 2020, Computers & Fluids
  • Machine Learning Approaches for the Solution of the Riemann Problem in Fluid Dynamics: a Case Study, 2024, Communications on Applied Mathematics and Computation

Shashkov has collaborated frequently with several researchers, including Konstantin Lipnikov, Mack Kenamond, Dmitri Kuzmin, Jan Velechovský, and Evgeny Kikinzon, with whom multiple joint publications have been produced.

Recognition of Shashkov's work includes being named a SIAM Fellow in 2014 for contributions to the development of mimetic finite difference methods for nonlinear systems of partial differential equations.

Best Publications

  • The Construction of Compatible Hydrodynamics Algorithms Utilizing Conservation of Total Energy

    E.J. Caramana;D.E. Burton;M.J. Shashkov;P.P. Whalen

  • Mimetic finite difference method

    Konstantin Lipnikov;Gianmarco Manzini;Mikhail Shashkov

  • Conservative Finite-Difference Methods on General Grids

    Mikhail Shashkov

  • Convergence of the Mimetic Finite Difference Method for Diffusion Problems on Polyhedral Meshes

    Franco Brezzi;Konstantin Lipnikov;Mikhail Shashkov

  • Formulations of Artificial Viscosity for Multi-dimensional Shock Wave Computations

    E.J. Caramana;M.J. Shashkov;P.P. Whalen

  • Monotone finite volume schemes for diffusion equations on unstructured triangular and shape-regular polygonal meshes

    K. Lipnikov;M. Shashkov;D. Svyatskiy;Yu. Vassilevski

  • Natural discretizations for the divergence, gradient, and curl on logically rectangular grids☆

    J.M. Hyman;M. Shashkov

  • The Numerical Solution of Diffusion Problems in Strongly Heterogeneous Non-isotropic Materials

    James Hyman;Mikhail Shashkov;Stanly Steinberg

  • Solving Diffusion Equations with Rough Coefficients in Rough Grids

    Mikhail Shashkov;Stanly Steinberg

  • Multi-material interface reconstruction on generalized polyhedral meshes

    Hyung Taek Ahn;Mikhail Shashkov

  • Second-order sign-preserving conservative interpolation (remapping) on general grids

    L. G. Margolin;Mikhail Shashkov

  • Reconstruction of multi-material interfaces from moment data

    Vadim Dyadechko;Mikhail Shashkov

  • Elimination of Artificial Grid Distortion and Hourglass-Type Motions by Means of Lagrangian Subzonal Masses and Pressures

    E.J. Caramana;M.J. Shashkov

  • A tensor artificial viscosity using a mimetic finite difference algorithm

    J. C. Campbell;M. J. Shashkov

  • Reference Jacobian optimization-based rezone strategies for arbitrary Lagrangian Eulerian methods

    Patrick Knupp;Len G. Margolin;Mikhail Shashkov

  • A subcell remapping method on staggered polygonal grids for arbitrary-Lagrangian-Eulerian methods

    Raphaël Loubère;Mikhail J. Shashkov

  • Arbitrary Lagrangian-Eulerian methods for modeling high-speed compressible multimaterial flows

    Andrew J. Barlow;Pierre-Henri Maire;William J. Rider;Robert N. Rieben

  • Mimetic Finite Difference Methods for Diffusion Equations

    J. Hyman;M. Shashkov;S. Steinberg

  • A new discretization methodology for diffusion problems on generalized polyhedral meshes

    Franco Brezzi;Konstantin Lipnikov;Mikhail Shashkov;Valeria Simoncini

  • Adjoint operators for the natural discretizations of the divergence gradient and curl on logically rectangular grids

    James M. Hyman;Mikhail Shashkov

  • Mimetic Discretizations for Maxwell's Equations

    James M. Hyman;Mikhail Shashkov

Frequent Co-Authors

Konstantin Lipnikov
Konstantin Lipnikov Los Alamos National Laboratory
James M. Hyman
James M. Hyman Tulane University
Guglielmo Scovazzi
Guglielmo Scovazzi Duke University
Pavel B. Bochev
Pavel B. Bochev Sandia National Laboratories
Gianmarco Manzini
Gianmarco Manzini Los Alamos National Laboratory
Ivan Yotov
Ivan Yotov University of Pittsburgh
Yuri Bazilevs
Yuri Bazilevs Brown University
David J. Benson
David J. Benson University of California, San Diego
Franco Brezzi
Franco Brezzi National Research Council (CNR)
Hong Luo
Hong Luo North Carolina State University

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