World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
40
Citations
7338
World Ranking
2038
National Ranking
15

Mikhail V. Solodov 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 V. Solodov 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: 129 publications — 26th percentile

26% of scientists in this discipline score the same or lower.

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

Mikhail V. Solodov 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 V. Solodov 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: 40 D-Index — 45th percentile

45% of scientists in this discipline score the same or lower.

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

Overview

Mikhail V. Solodov is affiliated with the Instituto Nacional de Matemática Pura e Aplicada in Brazil. The research work is situated primarily in the fields of Mathematics and Engineering, with a particular focus on Numerical Analysis, Computational Theory and Mathematics, Computational Mechanics, Management Science and Operations Research, and Electrical and Electronic Engineering.

Their research covers a broad range of topics, prominently including Advanced Optimization Algorithms Research, Optimization and Variational Analysis, Iterative Methods for Nonlinear Equations, Risk and Portfolio Optimization, Sparse and Compressive Sensing Techniques, Electric Power System Optimization, and Matrix Theory and Algorithms.

Frequent coauthors collaborating with Mikhail V. Solodov include:

  • A. F. Izmailov
  • Claudia Sagastizábal
  • Pedro Augusto Pereira Borges
  • Andreas Fischer
  • Felipe Atenas

Notable publication venues where this researcher has frequently published are:

  • Computational Optimization and Applications
  • SIAM Journal on Optimization
  • Mathematical Programming
  • Journal of Optimization Theory and Applications
  • Set-Valued and Variational Analysis

Key recent papers authored or co-authored by Mikhail V. Solodov include:

  • The Levenberg-Marquardt method: an overview of modern convergence theories and more (2024), published in Computational Optimization and Applications
  • A regularized smoothing method for fully parameterized convex problems with applications to convex and nonconvex two-stage stochastic programming (2020), published in Mathematical Programming
  • Unit stepsize for the Newton method close to critical solutions (2020), published in Mathematical Programming
  • Accelerating convergence of the globalized Newton method to critical solutions of nonlinear equations (2020), published in Computational Optimization and Applications
  • A Unified Analysis of Descent Sequences in Weakly Convex Optimization, Including Convergence Rates for Bundle Methods (2023), published in SIAM Journal on Optimization

Best Publications

  • A New Projection Method for Variational Inequality Problems

    M. V. Solodov;B. F. Svaiter

  • Forcing strong convergence of proximal point iterations in a Hilbert space

    Mikhail V. Solodov;Benar Fux Svaiter

  • Modified Projection-Type Methods for Monotone Variational Inequalities

    Michael V. Solodov;Paul Tseng

  • A HYBRID APPROXIMATE EXTRAGRADIENT - PROXIMAL POINT ALGORITHM USING THE ENLARGEMENT OF A MAXIMAL MONOTONE OPERATOR

    M. V. Solodov;B. F. Svaiter

  • A hybrid projection-proximal point algorithm.

    M. V. Solodov;B. F. Svaiter

  • An Inexact Hybrid Generalized Proximal Point Algorithm and Some New Results on the Theory of Bregman Functions

    M. V. Solodov;B. F. Svaiter

  • Nonlinear complementarity as unconstrained and constrained minimization

    O. L. Mangasarian;M. V. Solodov

  • Newton-Type Methods for Optimization and Variational Problems

    Alexey F. Izmailov;Mikhail V. Solodov

  • On the projected subgradient method for nonsmooth convex optimization in a Hilbert space

    Ya. I. Alber;A. N. Iusem;M. V. Solodov

  • A UNIFIED FRAMEWORK FOR SOME INEXACT PROXIMAL POINT ALGORITHMS

    M. V. Solodov;B. F. Svaiter

  • Incremental Gradient Algorithms with Stepsizes Bounded Away from Zero

    M. V. Solodov

  • Serial and parallel backpropagation convergence via nonmonotone perturbed minimization

    O.L. Mangasarian;M.V. Solodov

  • Error bounds for proximal point subproblems and associated inexact proximal point algorithms

    Mikhail V. Solodov;Benar Fux Svaiter

  • Error stability properties of generalized gradient-type algorithms

    M. V. Solodov;S. K. Zavries

  • An Infeasible Bundle Method for Nonsmooth Convex Constrained Optimization without a Penalty Function or a Filter

    Claudia Sagastizábal;Mikhail Solodov

  • Local Convergence of Exact and Inexact Augmented Lagrangian Methods under the Second-Order Sufficient Optimality Condition

    Damián R. Fernández;Mikhail V. Solodov

  • A bundle-filter method for nonsmooth convex constrained optimization

    Elizabeth Karas;Ademir Ribeiro;Claudia Sagastizábal;Mikhail Solodov

  • Stabilized SQP revisited

    A. F. Izmailov;M. V. Solodov

  • A proximal bundle method for nonsmooth nonconvex functions with inexact information

    W. Hare;C. Sagastizábal;M. Solodov

  • Mathematical Programs with Vanishing Constraints: Optimality Conditions, Sensitivity, and a Relaxation Method

    Alexey F. Izmailov;Mikhail V. Solodov

Frequent Co-Authors

Claudia Sagastizábal
Claudia Sagastizábal State University of Campinas
Benar Fux Svaiter
Benar Fux Svaiter Instituto Nacional de Matemática Pura e Aplicada
Olvi L. Mangasarian
Olvi L. Mangasarian University of Wisconsin–Madison
Michael C. Ferris
Michael C. Ferris University of Wisconsin–Madison
Alfredo N. Iusem
Alfredo N. Iusem Fundação Getulio Vargas

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