World's Best Scientists 2026 revealed!
Robert Scheichl

Robert Scheichl

D-Index & Metrics

Mathematics

D-Index
34
Citations
4846
World Ranking
2912
National Ranking
177

Robert Scheichl 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 Robert Scheichl 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.

Robert Scheichl 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 Robert Scheichl 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: 34 D-Index — 21st percentile

21% of scientists in this discipline score the same or lower.

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

Overview

Robert Scheichl is affiliated with Heidelberg University in Germany and has an extensive research portfolio primarily situated in the fields of Engineering, Computer Science, and Mathematics. Their work encompasses a range of specialized subfields including Computational Theory and Mathematics, Computational Mechanics, Statistics, Probability and Uncertainty, Mechanics of Materials, and Numerical Analysis.

The research contributions by Scheichl focus on advanced numerical methods and computational modeling. Key topics within their work include:

  • Advanced Numerical Methods in Computational Mathematics
  • Probabilistic and Robust Engineering Design
  • Advanced Mathematical Modeling in Engineering
  • Mathematical Approximation and Integration
  • Numerical methods in engineering
  • Markov Chains and Monte Carlo Methods
  • Composite Material Mechanics

The scientist has published papers in multiple frequently targeted venues, reflecting the interdisciplinary nature of their work. These venues include:

  • arXiv (Cornell University)
  • Journal of Computational Physics
  • IMA Journal of Numerical Analysis
  • SIAM Journal on Numerical Analysis
  • SIAM/ASA Journal on Uncertainty Quantification

Among the recent papers authored or coauthored by Scheichl are:

  • Novel Design and Analysis of Generalized Finite Element Methods Based on Locally Optimal Spectral Approximations, 2022, SIAM Journal on Numerical Analysis
  • Multilevel Monte Carlo simulations of composite structures with uncertain manufacturing defects, 2020, Probabilistic Engineering Mechanics
  • Multilevel Delayed Acceptance MCMC, 2023, SIAM/ASA Journal on Uncertainty Quantification
  • Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format, 2022, SIAM/ASA Journal on Uncertainty Quantification
  • A fully adaptive multilevel stochastic collocation strategy for solving elliptic PDEs with random data, 2020, Journal of Computational Physics

Collaborations have been a significant aspect of Scheichl's career, frequently working with other researchers in related domains. Common coauthors include:

  • Chupeng Ma
  • Tim Dodwell
  • Linus Seelinger
  • Alexander D. Gilbert
  • Peter Bastian

Best Publications

  • Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients

    K. A. Cliffe;M. B. Giles;R. Scheichl;A. L. Teckentrup

  • Further analysis of multilevel Monte Carlo methods for elliptic PDEs with random coefficients

    A. L. Teckentrup;R. Scheichl;M. B. Giles;E. Ullmann

  • Finite Element Error Analysis of Elliptic PDEs with Random Coefficients and Its Application to Multilevel Monte Carlo Methods

    Julia Charrier;Robert Scheichl;Aretha L. Teckentrup

  • Abstract robust coarse spaces for systems of PDEs via generalized eigenproblems in the overlaps

    N. Spillane;V. Dolean;P. Hauret;F. Nataf

  • Quasi-Monte Carlo methods for elliptic PDEs with random coefficients and applications

    I. G. Graham;F. Y. Kuo;D. Nuyens;R. Scheichl

  • Domain decomposition for multiscale PDEs

    I. G. Graham;P. O. Lechner;R. Scheichl

  • Quasi-Monte Carlo finite element methods for elliptic PDEs with lognormal random coefficients

    I. G. Graham;F. Y. Kuo;J. A. Nichols;R. Scheichl

  • A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow

    Tim J. Dodwell;Christian Ketelsen;Robert Scheichl;Aretha L. Teckentrup

  • Analysis of a two-level Schwarz method with coarse spaces based on local Dirichlet-to-Neumann maps

    Victorita Dolean;Frédéric Nataf;Robert Scheichl;Nicole Spillane

  • Analysis of FETI methods for multiscale PDEs

    Clemens Pechstein;Robert Scheichl

  • Multilevel Quasi-Monte Carlo methods for lognormal diffusion problems

    Frances Y. Kuo;Robert Scheichl;Christoph Schwab;Ian H. Sloan

  • Algebraic multigrid for discontinuous Galerkin discretizations of heterogeneous elliptic problems

    Peter Bastian;Markus Blatt;Robert Scheichl

  • Decoupling and Block Preconditioning for Sedimentary Basin Simulations

    Robert Scheichl;R. Masson;J. Wendebourg

  • Massively parallel solvers for elliptic partial differential equations in numerical weather and climate prediction

    Eike H. Müller;Robert Scheichl

  • Weighted Poincaré inequalities

    Clemens Pechstein;Robert Scheichl

  • Analysis of FETI methods for multiscale PDEs. Part II: interface variation

    Clemens Pechstein;Robert Scheichl

  • A Stein variational Newton method

    Gianluca Detommaso;Tiangang Cui;Youssef M. Marzouk;Alessio Spantini

  • Robust domain decomposition algorithms for multiscale PDEs

    I.G. Graham;R. Scheichl

  • Additive Schwarz with aggregation-based coarsening for elliptic problems with highly variable coefficients

    R. Scheichl;E. Vainikko

  • Parallel computation of flow in heterogeneous media modelled by mixed finite elements

    K. A. Cliffe;I. G. Graham;R. Scheichl;L. Stals

  • A Stein variational Newton method

    Gianluca Detommaso;Tiangang Cui;Alessio Spantini;Youssef Marzouk

  • Numerical Analysis of Multiscale Problems

    Ivan G. Graham;Thomas Y. Hou;Omar Lakkis;Robert Scheichl

Frequent Co-Authors

Ivan G. Graham
Ivan G. Graham University of Bath
Frances Y. Kuo
Frances Y. Kuo University of New South Wales
Ian H. Sloan
Ian H. Sloan University of New South Wales
Michael B. Giles
Michael B. Giles University of Oxford
Andreas E. Kyprianou
Andreas E. Kyprianou University of Warwick
Raphael T. Haftka
Raphael T. Haftka University of Florida
Nam H. Kim
Nam H. Kim University of Florida
Leroy Gardner
Leroy Gardner Imperial College London
Barbara Wohlmuth
Barbara Wohlmuth Technical University of Munich

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