World's Best Scientists 2026 revealed!
Robert Scheichl

Robert Scheichl

D-Index & Metrics

Mathematics

D-Index
34
Citations
4846
World Ranking
2911
National Ranking
177

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
Mark Girolami
Mark Girolami University of Cambridge
Leroy Gardner
Leroy Gardner Imperial College London
Barbara Wohlmuth
Barbara Wohlmuth Technical University of Munich

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