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Andreas Prohl 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 Andreas Prohl 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: 82 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+

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

Andreas Prohl 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 Andreas Prohl 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: 137 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+

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

Overview

Andreas Prohl is affiliated with the University of Tübingen in Germany and focuses on research primarily within the fields of Economics, Econometrics and Finance. Their scholarly contributions span several related subfields including Finance, Computational Theory and Mathematics, Computational Mechanics, Statistics, Probability and Uncertainty, and Statistics and Probability.

The research topics that dominate Prohl's work encompass stochastic processes and financial applications, advanced mathematical modeling in engineering, advanced numerical methods in computational mathematics, probabilistic and robust engineering design, risk and portfolio optimization, solidification and crystal growth phenomena, and statistical methods and inference.

Frequent collaboration with other researchers is a notable aspect of Prohl's academic activity. Key coauthors include Dominic Breit, Yanqing Wang, Fabian Merle, and Martin Ondreját.

Prohl has contributed to publications in several venues, with repeated appearances in:

  • arXiv (Cornell University)
  • IMA Journal of Numerical Analysis
  • Numerische Mathematik
  • Stochastic Partial Differential Equations Analysis and Computations
  • ESAIM Control Optimisation and Calculus of Variations

Significant recent papers authored or coauthored by Prohl cover topics in stochastic partial differential equations, numerical approximations, and stochastic control problems. Selected works include:

  • Strong rates of convergence for a space-time discretization of the backward stochastic heat equation, and of a linear-quadratic control problem for the stochastic heat equation, 2021, ESAIM Control Optimisation and Calculus of Variations

Other recent relevant publications, though not authored by Prohl but representative of the research themes they engage with, include:

  • Optimally convergent mixed finite element methods for the stochastic Stokes equations, 2021, IMA Journal of Numerical Analysis
  • Numerical approximation of nonlinear SPDE's, 2022, Stochastic Partial Differential Equations Analysis and Computations
  • Numerical approximation of the stochastic Cahn-Hilliard equation near the sharp interface limit, 2021, Numerische Mathematik
  • Error Analysis for 2D Stochastic Navier-Stokes Equations in Bounded Domains with Dirichlet Data, 2023, Foundations of Computational Mathematics

Best Publications

  • Numerical analysis of the Allen-Cahn equation and approximation for mean curvature flows

    Xiaobing Feng;Andreas Prohl

  • Projection and Quasi-Compressibility Methods for Solving the Incompressible Navier-Stokes Equations

    Andreas Prohl

  • Error analysis of a mixed finite element method for the Cahn-Hilliard equation

    Xiaobing Feng;Andreas Prohl

  • Recent Developments in the Modeling, Analysis, and Numerics of Ferromagnetism

    Martin Kruzík;Andreas Prohl

  • Convergence of an Implicit Finite Element Method for the Landau--Lifshitz--Gilbert Equation

    Sören Bartels;Andreas Prohl

  • Convergent finite element discretizations of the nonstationary incompressible magnetohydrodynamics system

    Andreas Prohl

  • Finite Element Approximations of the Ericksen-Leslie Model for Nematic Liquid Crystal Flow

    Roland Becker;Xiaobing Feng;Andreas Prohl

  • Analysis of a fully discrete finite element method for the phase field model and approximation of its sharp interface limits

    Xiaobing Feng;Andreas Prohl

  • Finite-element-based discretizations of the incompressible Navier–Stokes equations with multiplicative random forcing

    Zdzislaw Brzeźniak;Erich Carelli;Andreas Prohl

  • Analysis of total variation flow and its finite element approximations

    Xiaobing Feng;Andreas Prohl

  • Rates of Convergence for Discretizations of the Stochastic Incompressible Navier--Stokes Equations

    Erich Carelli;Andreas Prohl

  • Convergent discretizations for the Nernst–Planck–Poisson system

    Andreas Prohl;Markus Schmuck

  • Numerical analysis of the Cahn-Hilliard equation and approximation for the Hele-Shaw problem

    Xiaobing Feng;Andreas Prohl

  • Numerical analysis of an explicit approximation scheme for the Landau-Lifshitz-Gilbert equation

    Soeren Bartels;Soeren Bartels;Joy Ko;Andreas Prohl

  • Constraint preserving implicit finite element discretization of harmonic map flow into spheres

    Soeren Bartels;Andreas Prohl

  • Numerical analysis of relaxed micromagnetics by penalised finite elements

    Carsten Carstensen;Andreas Prohl

  • Optimal Strong Rates of Convergence for a Space-Time Discretization ofthe Stochastic Allen–Cahn Equation with Multiplicative Noise

    Ananta K. Majee;Andreas Prohl

  • A convergent finite-element-based discretization of the stochastic Landau–Lifshitz–Gilbert equation

    L̆ubomír Baňas;Zdzislaw Brzeźniak;Mikhail Neklyudov;Andreas Prohl

  • A Convergent Implicit Finite Element Discretization of the Maxwell-Landau-Lifshitz-Gilbert Equation

    L'ubomír Baňas;Sören Bartels;Andreas Prohl

  • Rate of convergence of regularization procedures and finite element approximations for the total variation flow

    X. Feng;M. von Oehsen;A. Prohl

Frequent Co-Authors

John W. Barrett
John W. Barrett University of Nottingham
Zdzisław Brzeźniak
Zdzisław Brzeźniak University of York
Carsten Carstensen
Carsten Carstensen Humboldt-Universität zu Berlin
Christian Lubich
Christian Lubich University of Tübingen

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