David J. Silvester

David J. Silvester

Manchester University

H-index: 34

North America-United States

About David J. Silvester

David J. Silvester, With an exceptional h-index of 34 and a recent h-index of 18 (since 2020), a distinguished researcher at Manchester University, specializes in the field of Mathematics, Numerical Analysis, Scientific Computing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Robin-type domain decomposition with stabilized mixed approximation for incompressible flow

IFISS3D: A computational laboratory for investigating finite element approximation in three dimensions

Efficient adaptive stochastic collocation strategies for advection–diffusion problems with uncertain inputs

New Directions in Applied Linear Algebra

Error estimation and adaptivity for stochastic collocation finite elements Part II: multilevel approximation

Fast solution of incompressible flow problems with two-level pressure approximation

Robust a posteriori error estimation for mixed finite element approximation of linear poroelasticity

Robust a posteriori error estimation for parameter-dependent linear elasticity equations

David J. Silvester Information

University

Position

Professor of Mathematics

Citations(all)

7407

Citations(since 2020)

1993

Cited By

6368

hIndex(all)

34

hIndex(since 2020)

18

i10Index(all)

59

i10Index(since 2020)

35

Email

University Profile Page

Manchester University

Google Scholar

View Google Scholar Profile

David J. Silvester Skills & Research Interests

Mathematics

Numerical Analysis

Scientific Computing

Top articles of David J. Silvester

Title

Journal

Author(s)

Publication Date

Robin-type domain decomposition with stabilized mixed approximation for incompressible flow

Computers & Mathematics with Applications

Yani Feng

Qifeng Liao

David Silvester

2023/10/1

IFISS3D: A computational laboratory for investigating finite element approximation in three dimensions

ACM Transactions on Mathematical Software

Georgios Papanikos

Catherine E Powell

David J Silvester

2023/9/19

Efficient adaptive stochastic collocation strategies for advection–diffusion problems with uncertain inputs

Journal of Scientific Computing

Benjamin M Kent

Catherine E Powell

David J Silvester

Małgorzata J Zimoń

2023/9

New Directions in Applied Linear Algebra

John Pearson

Jennifer Pestana

David Silvester

Valeria Simoncini

2023/8/27

Error estimation and adaptivity for stochastic collocation finite elements Part II: multilevel approximation

SIAM Journal on Scientific Computing

Alex Bespalov

David Silvester

2023/4/30

Fast solution of incompressible flow problems with two-level pressure approximation

arXiv preprint arXiv:2303.10233

Jennifer Pestana

David J Silvester

2023/3/17

Robust a posteriori error estimation for mixed finite element approximation of linear poroelasticity

IMA Journal of Numerical Analysis

Arbaz Khan

David J Silvester

2021/7

Robust a posteriori error estimation for parameter-dependent linear elasticity equations

Mathematics of Computation

Arbaz Khan

Alex Bespalov

Catherine Powell

David Silvester

2021/3

T-IFISS: a toolbox for adaptive FEM computation

Computers & Mathematics with Applications

Alex Bespalov

Leonardo Rocchi

David Silvester

2021/1/1

A fully adaptive multilevel stochastic collocation strategy for solving elliptic PDEs with random data

Journal of Computational Physics

Jens Lang

Robert Scheichl

David Silvester

2020/10/15

A locally mass conserving quadratic velocity, linear pressure element

arXiv preprint arXiv:2001.11878

Ronald W Thatcher

David J Silvester

2020/1/31

See List of Professors in David J. Silvester University(Manchester University)

Co-Authors

H-index: 49
Valeria Simoncini

Valeria Simoncini

Università degli Studi di Bologna

H-index: 42
Howard Elman

Howard Elman

University of Maryland, Baltimore

H-index: 41
John W Chew

John W Chew

University of Surrey

H-index: 34
David Kay

David Kay

University of Oxford

H-index: 32
John Dold

John Dold

Manchester University

academic-engine