World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
34
Citations
5775
World Ranking
2892
National Ranking
66

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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