World's Best Scientists 2026 revealed!
Award Badge
Mathematics
USA
2026

D-Index & Metrics

Mathematics

D-Index
75
Citations
33760
World Ranking
198
National Ranking
117

Computer Science

D-Index
68
Citations
31172
World Ranking
2031
National Ranking
1028

Linda R. Petzold publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Linda R. Petzold sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 272 publications — 81st percentile

81% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Linda R. Petzold D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Linda R. Petzold sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 75 D-Index — 95th percentile

95% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Mathematics in United States Leader Award
  • 2025 - Research.com Mathematics in United States Leader Award
  • 2013 - SIAM/ACM Prize in Computational Science and Engineering For her pioneering research in methods for the computational solution of differential-algebraic equations, their incorporation into widely distributed software and scientific applications, and her significant accomplishments in pioneering computational science and engineering education.
  • 2011 - ACM Fellow For contributions to computational science.
  • 2009 - SIAM Fellow For contributions to numerical ordinary differential equations and differential-algebraic equations and computational science.
  • 2007 - Fellow of the American Society of Mechanical Engineers
  • 2005 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2004 - Member of the National Academy of Engineering For advances in the numerical solution of differential/algebraic equations and their incorporation into widely distributed software.

Overview

Linda R. Petzold is affiliated with the University of California, Santa Barbara in the United States. Their primary field of study is Computer Science, with a focus on several subfields including Artificial Intelligence, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Molecular Biology, and Statistical and Nonlinear Physics.

The main topics covered in their research are:

  • Topic Modeling
  • Neural dynamics and brain function
  • Neuroscience and Neural Engineering
  • Model Reduction and Neural Networks
  • Neural Networks and Applications
  • Natural Language Processing Techniques
  • Machine Learning in Healthcare

Frequent venues for their publications include:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Chaos An Interdisciplinary Journal of Nonlinear Science
  • PLoS ONE
  • PLoS Computational Biology

Linda R. Petzold has contributed to notable papers such as:

  • "Functional neuronal circuitry and oscillatory dynamics in human brain organoids," 2022, Nature Communications
  • "Experimentally Validated Reconstruction and Analysis of a Genome-Scale Metabolic Model of an Anaerobic Neocallimastigomycota Fungus," 2021, mSystems
  • "Epigenetic biotypes of post-traumatic stress disorder in war-zone exposed veteran and active duty males," 2020, Molecular Psychiatry
  • "An empirical study on the robustness of the segment anything model (SAM)," 2024, Pattern Recognition
  • "Interpretable polynomial neural ordinary differential equations," 2023, Chaos An Interdisciplinary Journal of Nonlinear Science

Co-authorship has frequently involved collaborations with:

  • Paul K. Hansma
  • Xianjun Yang
  • Colby Fronk
  • Kenneth S. Kosik
  • Rachael A. Callcut

Their work has been recognized with several awards, including:

  • SIAM/ACM Prize in Computational Science and Engineering (2013), acknowledging research in computational methods for differential-algebraic equations and education advancements
  • ACM Fellow (2011) for contributions to computational science
  • SIAM Fellow (2009) for work in numerical ordinary differential equations, differential-algebraic equations, and computational science
  • Fellow of the American Society of Mechanical Engineers (2007)
  • Fellow of the American Association for the Advancement of Science (AAAS) (2005)
  • Member of the National Academy of Engineering (2004) for advances in numerical solutions of differential/algebraic equations and software incorporation

Best Publications

  • Numerical solution of initial-value problems in differential-algebraic equations

    Kathryn Eleda Brenan;S. L. Campbell;Linda Ruth Petzold

  • Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations

    Uri M. Ascher;Linda R. Petzold

  • Description of DASSL: a differential/algebraic system solver

    L.R. Petzold

  • Automatic Selection of Methods for Solving Stiff and Nonstiff Systems of Ordinary Differential Equations

    Linda Petzold

  • Efficient step size selection for the tau-leaping simulation method

    Yang Cao;Daniel T. Gillespie;Linda R. Petzold

  • Differential/Algebraic Equations are not ODE's

    Linda Petzold

  • ODE METHODS FOR THE SOLUTION OF DIFFERENTIAL/ALGEBRAIC SYSTEMS

    C. W. Gear;L. R. Petzold

  • The Slow-Scale Stochastic Simulation Algorithm

    Yang Cao;Daniel T. Gillespie;Linda R. Petzold

  • Using Krylov methods in the solution of large-scale differential-algebraic systems

    Peter N. Brown;Alan C. Hindmarsh;Linda R. Petzold

  • Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences

    Mark Alber;Adrian Buganza Tepole;William R. Cannon;Suvranu De

  • A New Look at Proper Orthogonal Decomposition

    Muruhan Rathinam;Linda R. Petzold

  • Stiffness in stochastic chemically reacting systems: The implicit tau-leaping method

    Muruhan Rathinam;Linda R. Petzold;Yang Cao;Daniel T. Gillespie

  • Efficient formulation of the stochastic simulation algorithm for chemically reacting systems

    Yang Cao;Hong Li;Linda Petzold

  • Improved leap-size selection for accelerated stochastic simulation

    Daniel T. Gillespie;Linda R. Petzold

  • Adjoint Sensitivity Analysis for Differential-Algebraic Equations: The Adjoint DAE System and Its Numerical Solution

    Yang Cao;Shengtai Li;Linda Petzold;Radu Serban

  • Perspective: Stochastic algorithms for chemical kinetics

    Daniel T. Gillespie;Andreas Hellander;Linda R. Petzold

  • Numerical methods and software for sensitivity analysis of differential-algebraic systems

    Timothy Maly;Linda R. Petzold

  • Avoiding negative populations in explicit Poisson tau-leaping.

    Yang Cao;Daniel T. Gillespie;Linda R. Petzold

  • Multiscale modeling meets machine learning: What can we learn?

    Grace C Y Peng;Mark Alber;Adrian Buganza Tepole;William R Cannon

  • Adaptive explicit-implicit tau-leaping method with automatic tau selection

    Yang Cao;Daniel T. Gillespie;Linda R. Petzold

  • Stabilization of Constrained Mechanical Systems with DAEs and Invariant Manifolds

    Uri M. Ascher;Hongsheng Chin;Linda R. Petzold;Sebastian Reich

  • Differential-algebraic equations

    Stephen L. Campbell;Vu Hoang Linh;Linda R. Petzold

Frequent Co-Authors

Francis J. Doyle
Francis J. Doyle Brown University
Uri M. Ascher
Uri M. Ascher University of British Columbia
Stephen L. Campbell
Stephen L. Campbell North Carolina State University
Mitchell J. Cohen
Mitchell J. Cohen University of Colorado Denver
Richard C. Alkire
Richard C. Alkire University of Illinois at Urbana-Champaign
Kenneth S. Kosik
Kenneth S. Kosik University of California, Santa Barbara
Igor Mezic
Igor Mezic University of California, Santa Barbara
Erik D. Herzog
Erik D. Herzog Washington University in St. Louis
Tresa M. Pollock
Tresa M. Pollock University of California, Santa Barbara

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

For students studying Mathematics in the USA, exploring related online degrees can broaden career opportunities and enhance skill sets. Business-oriented programs such as an what mba programs can i get into guide can help identify flexible MBA options that complement a math background.

If you’re seeking convenience without compromising quality, several easy online mba programs offer accessible paths to leadership roles in finance, analytics, or operations management. These programs typically have minimal entry barriers, making them a popular choice for working professionals.

For those interested in advanced business leadership, online dba programs provide an affordable route to doctoral-level expertise, particularly in data-driven decision-making and strategic management.

Mathematics graduates may also consider financial careers through a master of finance online. This degree builds on quantitative skills and opens doors to roles in investment management, risk analysis, and financial engineering.

Best Scientists Citing Linda R. Petzold

Trending Scientists

Recently Published Articles