World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
45
Citations
14020
World Ranking
1421
National Ranking
627

Engineering and Technology

D-Index
45
Citations
14070
World Ranking
5333
National Ranking
1490

Research.com Recognitions

  • 2014 - SIAM Fellow For contributions to numerical analysis and scientific computing including finite element methods, adaptive methods, reliability, and a posteriori error estimation.

Overview

Mark Ainsworth is affiliated with Brown University in the United States and has a multidisciplinary research profile bridging medicine and engineering. Their work spans several subfields including computational mechanics, infectious diseases, genetics, epidemiology, and mechanics of materials. This diverse expertise is reflected in the topics covered in their publications.

The main areas of research covered by Ainsworth include:

  • Inflammatory Bowel Disease
  • Advanced Numerical Methods in Computational Mathematics
  • COVID-19 Clinical Research Studies
  • Lattice Boltzmann Simulation Studies
  • Microscopic Colitis
  • Numerical methods in engineering
  • Long-Term Effects of COVID-19

Frequent collaborators associated with Ainsworth are:

  • P Frey
  • Sergio R. Idelsohn
  • Wolfgang A. Wall
  • Álvaro L. G. A. Coutinho
  • Kazuo Kashiyama

Ainsworth's research has been published primarily in specialized journals focused on computational methods and medicine, such as:

  • International Journal for Numerical Methods in Fluids
  • SIAM Journal on Scientific Computing
  • arXiv (Cornell University)
  • Computer Methods in Applied Mechanics and Engineering
  • Scandinavian Journal of Gastroenterology

Notable recent papers associated with the researcher include:

  • "Physical, cognitive, and mental health impacts of COVID-19 after hospitalisation (PHOSP-COVID): a UK multicentre, prospective cohort study" (2021), The Lancet Respiratory Medicine
  • "Azithromycin in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial" (2021), The Lancet
  • "Performance characteristics of five immunoassays for SARS-CoV-2: a head-to-head benchmark comparison" (2020), The Lancet Infectious Diseases
  • "Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study" (2022), The Lancet Respiratory Medicine
  • "A blood atlas of COVID-19 defines hallmarks of disease severity and specificity" (2022), Cell

The researcher received recognition as a SIAM Fellow in 2014 for contributions to numerical analysis and scientific computing including finite element methods, adaptive methods, reliability, and a posteriori error estimation.

Best Publications

  • A Posteriori Error Estimation in Finite Element Analysis

    Mark Ainsworth;J.Tinsley Oden

  • A Posteriori Error Estimation in Finite Element Analysis: Oden/A Posteriori

    Mark Ainsworth;J. Tinsley Oden

  • A unified approach to a posteriori error estimation using element residual methods

    Mark Ainsworth;J. Tinsley Oden

  • What is the fractional Laplacian? A comparative review with new results

    Anna Lischke;Guofei Pang;Mamikon A. Gulian;Fangying Song

  • Dispersive and dissipative behaviour of high order discontinuous Galerkin finite element methods

    Mark Ainsworth

  • Discrete Dispersion Relation for hp -Version Finite Element Approximation at High Wave Number

    Mark Ainsworth

  • Dispersive and Dissipative Properties of Discontinuous Galerkin Finite Element Methods for the Second-Order Wave Equation

    M. Ainsworth;P. Monk;W. Muniz

  • Analysis of the Zienkiewicz–Zhu a‐posteriori error estimator in the finite element method

    M. Ainsworth;J. Z. Zhu;A. W. Craig;O. C. Zienkiewicz

  • Hierarchic finite element bases on unstructured tetrahedral meshes

    Mark Ainsworth;Joe Coyle

  • Aspects of an adaptive hp-finite element method : Adaptive strategy, conforming approximation and efficient solvers

    Mark Ainsworth;Bill Senior

  • Analysis and Approximation of a Fractional Cahn--Hilliard Equation

    Mark Ainsworth;Zhiping Mao

  • A Posteriori Error Estimation for Discontinuous Galerkin Finite Element Approximation

    Mark Ainsworth

  • A Posteriori Error Estimators for the Stokes and Oseen Equations

    Mark Ainsworth;J. Tinsley Oden

  • A procedure for a posteriori error estimation for h-p finite element methods

    Mark Ainsworth;J. Tinsley Oden

  • Robust A Posteriori Error Estimation for Nonconforming Finite Element Approximation

    Mark Ainsworth

  • Hierarchic hp-edge element families for Maxwell's equations on hybrid quadrilateral/triangular meshes

    Mark Ainsworth;Joe Coyle

  • An a posteriori error estimate for finite element approximations of the Navier-Stokes equations

    J. Tinsley Oden;Weihan Wu;Mark Ainsworth

  • An adaptive refinement strategy for hp -finite element computations

    Mark Ainsworth;Bill Senior

  • A unified Petrov-Galerkin spectral method for fractional PDEs

    Mohsen Zayernouri;Mark Ainsworth;George Em Karniadakis

  • A posteriori error estimators in the finite element method

    Mark Ainsworth;Alan Craig

  • What Is the Fractional Laplacian

    Anna Lischke;Guofei Pang;Mamikon Gulian;Fangying Song

Frequent Co-Authors

Scott Klasky
Scott Klasky Oak Ridge National Laboratory
Norbert Podhorszki
Norbert Podhorszki Oak Ridge National Laboratory
George Em Karniadakis
George Em Karniadakis Brown University
Tahsin Kurc
Tahsin Kurc Stony Brook University
Manish Parashar
Manish Parashar University of Utah
Leszek Demkowicz
Leszek Demkowicz The University of Texas at Austin
J. T. Oden
J. T. Oden The University of Texas at Austin
Ian Foster
Ian Foster University of Chicago
O.C. Zienkiewicz
O.C. Zienkiewicz Swansea University
Carsten Carstensen
Carsten Carstensen Humboldt-Universität zu Berlin

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

Pursuing a degree in Mathematics opens doors to various advanced educational and career opportunities. Many students explore interdisciplinary fields that combine math with technology, business, or data science. For example, an MS in Digital Marketing degree cost USA programs provide insight into affordable pathways that pay well, merging analytical skills with marketing expertise.

Graduate education options like a one year MBA offer a fast-track to leadership roles, especially appealing for individuals seeking to blend quantitative skills with business acumen. For those concerned about time and cost efficiency, exploring whether can you transfer credits into an MBA program can be a strategic move to accelerate degree completion.

Additionally, the surge in demand for data professionals highlights the value of pursuing the best masters in data analytics programs. These programs enhance mathematical foundations with critical data skills, preparing graduates for roles in analytics, finance, and technology sectors.

Choosing the right online program that fits your career ambitions and financial considerations is crucial in today’s competitive market. Combining mathematics with these emerging fields ensures diverse, high-growth career pathways.

Best Scientists Citing Mark Ainsworth

Trending Scientists