World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
34
Citations
5775
World Ranking
2893
National Ranking
66

Frances Y. Kuo 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 Frances Y. Kuo 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: 137 publications — 31st percentile

31% of scientists in this discipline score the same or lower.

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

Frances Y. Kuo 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 Frances Y. Kuo 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

Frances Y. Kuo is affiliated with the University of New South Wales in Australia. Their research spans several areas within mathematics and engineering, with a primary focus on numerical analysis and computational methods.

Their work covers a variety of main fields of study including:

  • Mathematics
  • Engineering

Within these broader fields, Kuo's research concentrates on subfields such as:

  • Numerical Analysis
  • Statistics, Probability and Uncertainty
  • Computational Mechanics
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

The scientist's main topics of work include:

  • Mathematical Approximation and Integration
  • Probabilistic and Robust Engineering Design
  • Advanced Numerical Analysis Techniques
  • Advanced Numerical Methods in Computational Mathematics
  • Advanced Mathematical Modeling in Engineering
  • Nuclear reactor physics and engineering
  • Electromagnetic Scattering and Analysis

Kuo has published regularly in several academic venues, particularly in:

  • arXiv (Cornell University)
  • SIAM/ASA Journal on Uncertainty Quantification
  • Numerische Mathematik
  • Mathematics of Computation
  • SIAM Journal on Numerical Analysis

Recent notable papers include:

  • A Quasi-Monte Carlo Method for Optimal Control Under Uncertainty, 2021, SIAM/ASA Journal on Uncertainty Quantification
  • Quasi-Monte Carlo Finite Element Analysis for Wave Propagation in Heterogeneous Random Media, 2021, SIAM/ASA Journal on Uncertainty Quantification
  • MATHICSE Technical Report: Fast approximation by periodic kernel-based lattice-point interpolation with application in uncertainty quantification, 2020, Infoscience (Ecole Polytechnique Fédérale de Lausanne)
  • Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration, 2024, Numerische Mathematik
  • Function integration, reconstruction and approximation using rank-1 lattices, 2021, Mathematics of Computation

Frequent collaborators in Kuo's research include:

  • Ian H. Sloan
  • Dirk Nuyens
  • Alexander D. Gilbert
  • Vesa Kaarnioja
  • Abirami Srikumar

Best Publications

  • High-dimensional integration: The quasi-Monte Carlo way

    Josef Dick;Frances Y. Kuo;Ian H. Sloan

  • Remark on algorithm 659: Implementing Sobol's quasirandom sequence generator

    Stephen Joe;Frances Y. Kuo

  • Constructing Sobol Sequences with Better Two-Dimensional Projections

    Stephen Joe;Frances Y. Kuo

  • Quasi-Monte Carlo Finite Element Methods for a Class of Elliptic Partial Differential Equations with Random Coefficients

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

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

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

  • Component-by-component constructions achieve the optimal rate of convergence for multivariate integration in weighted Korobov and Sobolev spaces

    F. Y. Kuo

  • On decompositions of multivariate functions

    Frances Y. Kuo;Ian H. Sloan;Grzegorz W. Wasilkowski;Henryk Wozniakowski

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

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

  • Constructing Randomly Shifted Lattice Rules in Weighted Sobolev Spaces

    I. H. Sloan;F. Y. Kuo;S. Joe

  • Constructing Embedded Lattice Rules for Multivariate Integration

    Ronald Cools;Frances Y. Kuo;Dirk Nuyens

  • Application of Quasi-Monte Carlo Methods to Elliptic PDEs with Random Diffusion Coefficients: A Survey of Analysis and Implementation

    Frances Y. Kuo;Dirk Nuyens

  • Multi-level Quasi-Monte Carlo Finite Element Methods for a Class of Elliptic PDEs with Random Coefficients

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

  • HIGHER ORDER QMC GALERKIN DISCRETIZATION FOR PARAMETRIC OPERATOR EQUATIONS

    Josef Dick;Frances Y. Kuo;Quoc T. Le Gia;Dirk Nuyens

  • On the step-by-step construction of quasi: Monte Carlo integration rules that achieve strong tractability error bounds in weighted Sobolev spaces

    I. H. Sloan;F. Y. Kuo;S. Joe

  • Quasi-Monte Carlo methods for high dimensional integration - the standard (weighted Hilbert space) setting and beyond

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

  • Multilevel Quasi-Monte Carlo methods for lognormal diffusion problems

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

  • Higher Order QMC Petrov--Galerkin Discretization for Affine Parametric Operator Equations with Random Field Inputs

    Josef Dick;Frances Y. Kuo;Quoc Thong Le Gia;Dirk Nuyens

  • On the power of standard information for multivariate approximation in the worst case setting

    Frances Y. Kuo;Grzegorz W. Wasilkowski;Henryk Woniakowski

  • Construction algorithms for polynomial lattice rules for multivariate integration

    Josef Dick;Frances Y. Kuo;Friedrich Pillichshammer;Ian H. Sloan

  • Liberating the dimension

    Frances Y. Kuo;Ian H. Sloan;Grzegorz W. Wasilkowski;Henryk Woniakowski

Frequent Co-Authors

Ian H. Sloan
Ian H. Sloan University of New South Wales
Robert Scheichl
Robert Scheichl Heidelberg University
Henryk Woźniakowski
Henryk Woźniakowski University of Warsaw
Josef Dick
Josef Dick University of New South Wales
Ivan G. Graham
Ivan G. Graham University of Bath
Michael Griebel
Michael Griebel University of Bonn
Michael B. Giles
Michael B. Giles University of Oxford
Fabio Nobile
Fabio Nobile École Polytechnique Fédérale de Lausanne
Fred J. Hickernell
Fred J. Hickernell Illinois Institute of Technology

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