World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
8993
World Ranking
10512
National Ranking
4401

Overview

Michael A. Heroux is affiliated with Sandia National Laboratories in the United States. Their research primarily focuses on computer science and decision sciences, with particular emphasis on scientific computing and data management. Their work explores distributed and parallel computing systems, research data management practices, cloud computing and resource management, parallel computing and optimization techniques, data quality and management, and advanced data storage technologies.

The researcher has contributed to several recent papers, including:

  • Preparing sparse solvers for exascale computing, 2020, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  • How community software ecosystems can unlock the potential of exascale computing, 2021, Nature Computational Science
  • Research Software Science: Expanding the Impact of Research Software Engineering, 2022, Computing in Science & Engineering
  • Research Reproducibility, 2022, Computer
  • A Cast of Thousands: How the IDEAS Productivity Project Has Advanced Software Productivity and Sustainability, 2024, Computing in Science & Engineering

Frequent co-authors include:

  • Lois Curfman McInnes
  • James Willenbring
  • Rinku Gupta
  • Gregory R. Watson
  • Elsa Gonsiorowski

Michael A. Heroux has published extensively in several venues with multiple publications in Computing in Science & Engineering and arXiv (Cornell University). Other publication venues include Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Nature Computational Science, and Computer.

Their work spans subfields such as information systems and management, information systems, computer networks and communications, hardware and architecture, and management science and operations research.

Best Publications

  • An overview of the Trilinos project

    Michael A. Heroux;Roscoe A. Bartlett;Vicki E. Howle;Robert J. Hoekstra

  • An Updated Set of Basic Linear Algebra Subprograms (BLAS)

    Susan Blackford;James Demmel;Jack Dongarra;Iain Duff

  • The International Exascale Software Project roadmap

    Jack Dongarra;Pete Beckman;Terry Moore;Patrick Aerts

  • Improving Performance via Mini-applications

    Paul Stewart Crozier;Heidi K. Thornquist;Robert W. Numrich;Alan B. Williams

  • An overview of Trilinos.

    Kevin R. Long;Raymond Stephen Tuminaro;Roscoe Ainsworth Bartlett;Robert John Hoekstra

  • Enhancing reproducibility for computational methods.

    Victoria Stodden;Marcia McNutt;David H. Bailey;Ewa Deelman

  • Toward a New Metric for Ranking High Performance Computing Systems

    Sandia Report;Jack Dongarra;Michael A. Heroux

  • An overview of the sparse basic linear algebra subprograms: The new standard from the BLAS technical forum

    Iain S. Duff;Michael A. Heroux;Roldan Pozo

  • High-performance conjugate-gradient benchmark

    Jack Dongarra;Michael A Heroux;Piotr Luszczek

  • Big data and extreme-scale computing: Pathways to Convergence-Toward a shaping strategy for a future software and data ecosystem for scientific inquiry

    M. Asch;T. Moore;R. Badia;M. Beck

  • Solving Complex-Valued Linear Systems via Equivalent Real Formulations

    David Day;Michael A. Heroux

  • HPCG Benchmark: a New Metric for Ranking High Performance Computing Systems

    Jack Dongarra;Michael A. Heroux;Piotr Luszczek

  • GEMMW: a portable level 3 BLAS Winograd variant of Strassen's matrix-matrix multiply algorithm

    Craig C. Douglas;Michael Heroux;Gordon Slishman;Roger M. Smith

  • Trilinos users guide.

    James M. Willenbring;Michael Allen Heroux

  • Segmented Operations for Sparse Matrix Computation on Vector Multiprocessors

    Guy E. Blelloch;Michael A. Heroux;Marco Zagha

  • Applied Mathematics Research for Exascale Computing

    J Dongarra;J Hittinger;J Bell;L Chacon

  • Toward Local Failure Local Recovery Resilience Model using MPI-ULFM

    Keita Teranishi;Michael A. Heroux

  • ROBUST ALGEBRAIC PRECONDITIONERS USING IFPACK 3.0.

    Marzio Sala;Michael A. Heroux

  • Fault-tolerant iterative methods via selective reliability.

    Kurt Brian Ferreira;Patrick G. Bridges;Michael Allen Heroux;Mark Frederick Hoemmen

  • A new overview of the Trilinos project

    Michael A. Heroux;James M. Willenbring

  • Parallel processing for scientific computing

    Michael A. Heroux;Padma Raghavan;Horst D. Simon

Frequent Co-Authors

Jack Dongarra
Jack Dongarra University of Tennessee at Knoxville
Andrew G. Salinger
Andrew G. Salinger Sandia National Laboratories
Manish Parashar
Manish Parashar University of Utah
Piotr Luszczek
Piotr Luszczek University of Tennessee at Knoxville
Andrew A. Chien
Andrew A. Chien University of Chicago
Horst D. Simon
Horst D. Simon Lawrence Berkeley National Laboratory
Jacqueline H. Chen
Jacqueline H. Chen Sandia National Laboratories
Barry Smith
Barry Smith Argonne National Laboratory
John Shalf
John Shalf Lawrence Berkeley National Laboratory
Iain S. Duff
Iain S. Duff Rutherford Appleton Laboratory

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

Considering a degree in Computer Science? There are several flexible options available for students seeking alternative pathways. For those just starting out, online associates degrees can be a cost-effective way to gain foundational knowledge and skills, while also offering the flexibility to study at your own pace.

If affordability is a priority, explore institutions offering affordable online courses for a wide range of programs, including Computer Science and related technology fields. These courses help minimize student debt while maximizing academic potential.

Not every student’s GPA reflects their true potential. Fortunately, there are online graduate schools with low gpa requirements. These schools offer opportunities for career advancement and specialized study even if your undergraduate grades were not perfect.

Finally, Computer Science offers diverse career options, much like what you’ll find exploring what can you do with an environmental science major. From software engineering to IT management, the skills gained through online degrees can open doors to roles across industries.

Best Scientists Citing Michael A. Heroux

Trending Scientists

Recently Published Articles