World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
43
Citations
6905
World Ranking
1709
National Ranking
736

Gianmarco Manzini 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 Gianmarco Manzini 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: 175 publications — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Gianmarco Manzini 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 Gianmarco Manzini 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: 43 D-Index — 54th percentile

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

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

Overview

Gianmarco Manzini is affiliated with the Los Alamos National Laboratory in the United States. The primary focus of their research lies within the field of Engineering, with a significant concentration on Computational Mechanics. Their work spans several specialized subfields including Mechanics of Materials, Electrical and Electronic Engineering, Numerical Analysis, and Computational Theory and Mathematics.

Manzini has contributed extensively to the domain of advanced numerical techniques and mathematical modeling applied to engineering problems. Their research covers a broad spectrum of topics such as:

  • Advanced Numerical Methods in Computational Mathematics
  • Numerical methods in engineering
  • Electromagnetic Simulation and Numerical Methods
  • Computational Fluid Dynamics and Aerodynamics
  • Tensor decomposition and applications
  • Model Reduction and Neural Networks
  • Advanced Mathematical Modeling in Engineering

The scientist has authored numerous papers, frequently publishing in several academic venues. The most recurrent publication forums include arXiv (Cornell University), Computers & Mathematics with Applications, Computer Methods in Applied Mechanics and Engineering, Mathematics and Computers in Simulation, and the International Journal for Numerical Methods in Engineering.

Some notable papers authored by or involving Manzini are:

  • The NonConforming Virtual Element Method for the Stokes Equations (2022), OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
  • Coupling surface flow and subsurface flow in complex soil structures using mimetic finite differences (2020), Advances in Water Resources
  • The role of mesh quality and mesh quality indicators in the virtual element method (2021), Advances in Computational Mathematics
  • A Survey of Indicators for Mesh Quality Assessment (2023), Computer Graphics Forum
  • Virtual elements for Maxwell's equations (2021), Computers & Mathematics with Applications

Collaboration is a significant aspect of their research output. Frequent co-authors include:

  • Tommaso Sorgente
  • Silvia Biasotti
  • Michela Spagnuolo
  • Dibyendu Adak
  • Duc P. Truong

Best Publications

  • Mimetic finite difference method

    Konstantin Lipnikov;Gianmarco Manzini;Mikhail Shashkov

  • Discontinuous Galerkin approximations for elliptic problems

    F. Brezzi;G. Manzini;D. Marini;P. Pietra

  • The Mimetic Finite Difference Method for Elliptic Problems

    Lourenço Beirão da Veiga;Konstantin Lipnikov;Gianmarco Manzini

  • 3D Benchmark on Discretization Schemes for Anisotropic Diffusion Problems on General Grids

    Robert Eymard;Gérard Henry;Raphaèle Herbin;Florence Hubert

  • The nonconforming virtual element method

    Blanca Pilar Ayuso De Dios;Konstantin Lipnikov;Gianmarco Manzini

  • Conforming and nonconforming virtual element methods for elliptic problems

    Andrea Cangiani;Gianmarco Manzini;Oliver J. Sutton

  • New perspectives on polygonal and polyhedral finite element methods

    Gianmarco Manzini;Alessandro Russo;N. Sukumar

  • A virtual element method with arbitrary regularity

    Lourenco Beirão da Veiga;Gianmarco Manzini

  • The NonConforming Virtual Element Method for the Stokes Equations

    Andrea Cangiani;Vitaliy Gyrya;Gianmarco Manzini

  • Mass-conservative finite volume methods on 2-D unstructured grids for the Richards’ equation

    Gianmarco Manzini;Stefano Ferraris

  • The fully nonconforming virtual element method for biharmonic problems

    P. F. Antonietti;G. Manzini;M. Verani

  • Arbitrary-Order Nodal Mimetic Discretizations of Elliptic Problems on Polygonal Meshes

    L. Beirão da Veiga;K. Lipnikov;G. Manzini

  • Mimetic finite difference method for the Stokes problem on polygonal meshes

    L. Beirão da Veiga;V. Gyrya;K. Lipnikov;G. Manzini

  • A Second-Order Maximum Principle Preserving Finite Volume Method for Steady Convection-Diffusion Problems

    Enrico Bertolazzi;Gianmarco Manzini

  • Residual a posteriori error estimation for the Virtual Element Method for elliptic problems

    L. Beirão da Veiga;G. Manzini

  • Hourglass stabilization and the virtual element method

    A. Cangiani;G. Manzini;G. Manzini;A. Russo;N. Sukumar

  • A finite volume method for advection-diffusion problems in convection-dominated regimes

    Gianmarco Manzini;Alessandro Russo

  • Flux reconstruction and solution post-processing in mimetic finite difference methods

    Andrea Cangiani;Gianmarco Manzini

  • Analysis of the monotonicity conditions in the mimetic finite difference method for elliptic problems

    K. Lipnikov;G. Manzini;D. Svyatskiy

  • A CELL-CENTERED SECOND-ORDER ACCURATE FINITE VOLUME METHOD FOR CONVECTION–DIFFUSION PROBLEMS ON UNSTRUCTURED MESHES

    Enrico Bertolazzi;Gianmarco Manzini

  • The non-conforming virtual element method for the Stokes equations

    Andrea Cangiani;Vitaliy Gyrya;Gianmarco Manzini

  • The nonconforming virtual element method

    B. Ayuso de Dios;K. Lipnikov;G. Manzini

Frequent Co-Authors

Konstantin Lipnikov
Konstantin Lipnikov Los Alamos National Laboratory
L. Beirão da Veiga
L. Beirão da Veiga University of Milano-Bicocca
Mario Putti
Mario Putti University of Padua
N. Sukumar
N. Sukumar University of California, Davis
Mikhail Shashkov
Mikhail Shashkov Los Alamos National Laboratory
Franco Brezzi
Franco Brezzi National Research Council (CNR)
Jérôme Droniou
Jérôme Droniou University of Montpellier
Annalisa Buffa
Annalisa Buffa École Polytechnique Fédérale de Lausanne
Andrea Rinaldo
Andrea Rinaldo École Polytechnique Fédérale de Lausanne
Scott L. Painter
Scott L. Painter Oak Ridge National Laboratory

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students interested in Mathematics in the USA, exploring related online degrees can broaden career opportunities. Programs like data analysis programs build on mathematical foundations, preparing graduates for roles in data science and business intelligence.

Those aiming to expand their expertise into management and leadership may consider pursuing an MBA. Finding the easiest MBA program to get into can be a strategic choice for busy professionals seeking flexibility without compromising quality.

Similarly, for working individuals, the easiest online MBA program offers a convenient path to advance skills remotely while balancing other commitments.

For those focused on advanced business practice, affordable options like DBA programs online provide doctoral-level education that complements mathematical expertise with strategic business insights.

Best Scientists Citing Gianmarco Manzini

Trending Scientists

Recently Published Articles