World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
47
Citations
6903
World Ranking
1297
National Ranking
74

Boris N. Khoromskij 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 Boris N. Khoromskij 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: 158 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

Boris N. Khoromskij 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 Boris N. Khoromskij 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: 47 D-Index — 66th percentile

66% of scientists in this discipline score the same or lower.

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

Overview

Boris N. Khoromskij is affiliated with the Max Planck Institute for Mathematics in the Sciences in Germany. Their research spans key areas in computational mathematics, engineering, and physics, with a focus on numerical methods and tensor-based approaches to complex scientific problems.

Their scholarly output includes several papers published in notable venues. Recent publications include:

  • Numerical study in stochastic homogenization for elliptic partial differential equations: Convergence rate in the size of representative volume elements (2020, Numerical Linear Algebra with Applications)
  • Regularization of Poisson--Boltzmann Type Equations with Singular Source Terms Using the Range-Separated Tensor Format (2021, SIAM Journal on Scientific Computing)
  • Prospects of Tensor-Based Numerical Modeling of the Collective Electrostatics in Many-Particle Systems (2021, Computational Mathematics and Mathematical Physics)
  • Tensor product method for fast solution of optimal control problems with fractional multidimensional Laplacian in constraints (2020, Journal of Computational Physics)
  • Tensor method for optimal control problems constrained by fractional three-dimensional elliptic operator with variable coefficients (2021, Numerical Linear Algebra with Applications)

Frequent coauthors collaborating with Khoromskij include:

  • Venera Khoromskaia
  • Peter Benner
  • Volker Schulz
  • Cleophas Kweyu
  • Britta Schmitt

The main publication venues where Khoromskij's work appears are:

  • arXiv (Cornell University)
  • Numerical Linear Algebra with Applications
  • SIAM Journal on Scientific Computing
  • Computational Mathematics and Mathematical Physics
  • Journal of Computational Physics

Their research fields encompass:

  • Engineering
  • Physics and Astronomy
  • Mathematics

Within these fields, Khoromskij focuses on several subfields, such as:

  • Computational Mathematics
  • Computational Mechanics
  • Atomic and Molecular Physics, and Optics
  • Computational Theory and Mathematics
  • Mechanics of Materials

Key topics covered in their work relate to tensor and matrix computations and applied mathematical modeling, specifically:

  • Tensor decomposition and applications
  • Advanced Numerical Methods in Computational Mathematics
  • Electromagnetic Scattering and Analysis
  • Composite Material Mechanics
  • Advanced Mathematical Modeling in Engineering
  • Matrix Theory and Algorithms
  • Protein Structure and Dynamics

Best Publications

  • A sparse H -matrix arithmetic. Part II: application to multi-dimensional problems

    W. Hackbusch;B. N. Khoromskij

  • O(dlog N)-Quantics Approximation of N-d Tensors in High-Dimensional Numerical Modeling

    Boris N. Khoromskij

  • On H2-Matrices

    Wolfgang Hackbusch;Boris N. Khoromskij;Stefan A. Sauter

  • Tensors-structured Numerical Methods in Scientific Computing: Survey on Recent Advances

    Boris N. Khoromskij

  • Tensor-Structured Galerkin Approximation of Parametric and Stochastic Elliptic PDEs

    Boris N. Khoromskij;Christoph Schwab

  • Hierarchical Kronecker tensor-product approximations

    Wolfgang Hackbusch;Boris N. Khoromskij;Eugene E. Tyrtyshnikov

  • Low-rank Kronecker-product Approximation to Multi-dimensional Nonlocal Operators. Part I. Separable Approximation of Multi-variate Functions

    W. Hackbusch;N. Khoromskij

  • Low-Rank Explicit QTT Representation of the Laplace Operator and Its Inverse

    Vladimir A. Kazeev;Boris N. Khoromskij

  • Multigrid Accelerated Tensor Approximation of Function Related Multidimensional Arrays

    B. N. Khoromskij;V. Khoromskaia

  • Approximate iterations for structured matrices

    Wolfgang Hackbusch;Boris N. Khoromskij;Eugene E. Tyrtyshnikov

  • A sparse H -matrix arithmetic: general complexity estimates

    W. Hackbusch;B. N. Khoromskij

  • Solution of large scale algebraic matrix Riccati equations by use of hierarchical matrices

    L. Grasedyck;W. Hackbusch;B. N. Khoromskij

  • Fast Solution of Parabolic Problems in the Tensor Train/Quantized Tensor Train Format with Initial Application to the Fokker--Planck Equation

    Sergey V. Dolgov;Boris N. Khoromskij;Ivan V. Oseledets

  • Hierarchical Matrices based on a Weak Admissibility Criterion

    Wolfgang Hackbusch;Boris N. Khoromskij;Ronald Kriemann

  • Application of hierarchical matrices for computing the Karhunen–Loève expansion

    B. N. Khoromskij;A. Litvinenko;H. G. Matthies

  • Low rank Tucker-type tensor approximation to classical potentials

    Boris N. Khoromskij;Venera Khoromskaia

  • Computation of extreme eigenvalues in higher dimensions using block tensor train format

    Sergey V. Dolgov;Sergey V. Dolgov;Boris N. Khoromskij;Ivan V. Oseledets;Ivan V. Oseledets;Dmitry V. Savostyanov;Dmitry V. Savostyanov

  • Tensor-product approximation to operators and functions in high dimensions

    Wolfgang Hackbusch;Boris N. Khoromskij

  • Numerical Solution of the Hartree-Fock Equation in Multilevel Tensor-Structured Format

    B. N. Khoromskij;V. Khoromskaia;H.-J. Flad

  • H-matrix approximation for the operator exponential with applications

    Ivan P. Gavrilyuk;Wolfgang Hackbusch;Boris N. Khoromskij

  • Quantics-TT collocation approximation of parameter-dependent and stochastic elliptic PDEs

    Boris N. Khoromskij;Ivan V. Oseledets

Frequent Co-Authors

Wolfgang Hackbusch
Wolfgang Hackbusch Max Planck Institute for Mathematics in the Sciences
Ivan V. Oseledets
Ivan V. Oseledets Skolkovo Institute of Science and Technology
Eugene E. Tyrtyshnikov
Eugene E. Tyrtyshnikov Russian Academy of Sciences
Hermann G. Matthies
Hermann G. Matthies Technische Universität Braunschweig
Peter Benner
Peter Benner Max Planck Institute for Dynamics of Complex Technical Systems
Reinhold Schneider
Reinhold Schneider Technical University of Berlin
Stefan A. Sauter
Stefan A. Sauter University of Zurich
Felix Otto
Felix Otto Max Planck Institute for Mathematics in the Sciences
Bert Jüttler
Bert Jüttler Johannes Kepler University of Linz
Ulrich Langer
Ulrich Langer Johannes Kepler University of Linz

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, exploring related online degrees can open a wide range of career opportunities. Many professionals pursue specialized finance knowledge through an online masters in finance programs. These programs often blend quantitative analysis with practical financial skills, ideal for math-focused individuals.

Meanwhile, those aiming for leadership roles may consider a business-oriented degree. The shortest mba program online offers a quick yet comprehensive path to enhance management and strategic thinking abilities, directly complementing mathematical expertise.

Marketing is another promising field where a mathematical background is valuable. Pursuing a marketing masters online can combine analytical skills with market research and consumer behavior knowledge, leading to well-paid opportunities.

Finally, intensive programs like the one year mba program provide focused training for professionals seeking rapid career advancement without sacrificing depth or rigor.

Each of these paths leverages mathematical thinking in practical, high-demand sectors, making them excellent complements or alternatives to traditional math study.

Best Scientists Citing Boris N. Khoromskij

Trending Scientists

Recently Published Articles