World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
32
Citations
4780
World Ranking
9550
National Ranking
2704

Pras Pathmanathan publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Pras Pathmanathan sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 61 publications — 1st percentile

1% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Pras Pathmanathan D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Pras Pathmanathan sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 32 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Pras Pathmanathan is affiliated with the US Food and Drug Administration in the United States. Their research work centers primarily on medicine, with a strong focus on cardiology and cardiovascular medicine. The subfields of study associated with their publications also include statistics and probability, electrical and electronic engineering, biomedical engineering, and artificial intelligence.

The topics covered in Pras Pathmanathan's work reflect a concentration on cardiac electrophysiology and arrhythmias, statistical methods in clinical trials, cardiovascular function and risk factors, and ECG monitoring and analysis. Additionally, their research involves machine learning applications in healthcare, gene regulatory network analysis, and computational drug discovery methods.

Their frequent co-authors include:

  • Richard A. Gray (6 co-publications)
  • Steven Niederer (5 co-publications)
  • Brent A. Craven (4 co-publications)
  • Tina Morrison (3 co-publications)
  • Tammo Delhaas (3 co-publications)

Pras Pathmanathan has published in a variety of scientific journals, with multiple contributions in:

  • PLoS Computational Biology (4 publications)
  • Frontiers in Physiology (3 publications)
  • Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (2 publications)
  • Annals of Biomedical Engineering (2 publications)
  • European Heart Journal (1 publication)

Selected recent papers include:

  • The 'Digital Twin' to enable the vision of precision cardiology, 2020, European Heart Journal
  • Creation and application of virtual patient cohorts of heart models, 2020, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  • Chaste: Cancer, Heart and Soft Tissue Environment, 2020, The Journal of Open Source Software
  • Considering discrepancy when calibrating a mechanistic electrophysiology model, 2020, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  • A Quantitative Systems Pharmacology Perspective on the Importance of Parameter Identifiability, 2022, Bulletin of Mathematical Biology

Best Publications

  • The 'Digital Twin' to enable the vision of precision cardiology.

    Jorge Corral-Acero;Francesca Margara;Maciej Marciniak;Cristobal Rodero

  • Chaste: an open source C++ library for computational physiology and biology.

    Gary R. Mirams;Christopher J. Arthurs;Miguel O. Bernabeu;Rafel Bordas

  • Verification of cardiac tissue electrophysiology simulators using an N-version benchmark

    Steven Alexander Niederer;Eric Kerfoot;Alan P. Benson;Miguel O. Bernabeu

  • Chaste: A test-driven approach to software development for biological modelling☆

    Joe Pitt-Francis;Pras Pathmanathan;Miguel O. Bernabeu;Rafel Bordas

  • An integrative computational model for intestinal tissue renewal

    I. M.M. Van Leeuwen;I. M.M. Van Leeuwen;G. R. Mirams;A. Walter;A. Fletcher

  • Advancing Regulatory Science With Computational Modeling for Medical Devices at the FDA's Office of Science and Engineering Laboratories

    Tina M. Morrison;Pras Pathmanathan;Mariam Adwan;Edward Margerrison

  • Uncertainty and variability in computational and mathematical models of cardiac physiology

    Gary R. Mirams;Pras Pathmanathan;Richard A. Gray;Peter Challenor

  • Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges.

    Richard A. Gray;Pras Pathmanathan

  • Uncertainty and variability in models of the cardiac action potential: Can we build trustworthy models?

    Ross H. Johnstone;Eugene T.Y. Chang;Rémi Bardenet;Teun P. de Boer

  • A hybrid approach to multi-scale modelling of cancer

    J. M. Osborne;A. Walter;S. K. Kershaw;G. R. Mirams

  • A computational study of discrete mechanical tissue models.

    P Pathmanathan;J Cooper;A Fletcher;G Mirams

  • Computational assessment of drug‐induced effects on the electrocardiogram: from ion channel to body surface potentials

    Nejib Zemzemi;Nejib Zemzemi;Miguel O Bernabeu;Javier Saiz;Jonathan Cooper

  • Predicting Tumor Location by Modeling the Deformation of the Breast

    P. Pathmanathan;D.J. Gavaghan;J.P. Whiteley;S.J. Chapman

  • Chaste: using agile programming techniques to develop computational biology software

    Joe Pitt-Francis;Miguel O Bernabeu;Jonathan Cooper;Alan Garny

  • A numerical guide to the solution of the bidomain equations of cardiac electrophysiology

    Pras Pathmanathan;Miguel O. Bernabeu;Rafel Bordas;Jonathan Cooper

  • Creation and application of virtual patient cohorts of heart models

    S. A. Niederer;Y. Aboelkassem;C. D. Cantwell;C. Corrado

  • Chaste: Cancer, Heart and Soft Tissue Environment

    Fergus R. Cooper;Ruth E. Baker;Miguel O. Bernabeu;Rafel Bordas

  • Comprehensive Uncertainty Quantification and Sensitivity Analysis for Cardiac Action Potential Models.

    Pras Pathmanathan;Jonathan M. Cordeiro;Richard A. Gray

  • Predicting Tumour Location by Simulating Large Deformations of the Breast Using a 3D Finite Element Model and Nonlinear Elasticity

    Pras Pathmanathan;David Gavaghan;Jonathan Whiteley;Sir Michael Brady

  • A numerical method for cardiac mechanoelectric simulations.

    Pras Pathmanathan;Jonathan P. Whiteley

  • CARDIAC ELECTROMECHANICS: THE EFFECT OF CONTRACTION MODEL ON THE MATHEMATICAL PROBLEM AND ACCURACY OF THE NUMERICAL SCHEME

    P. Pathmanathan;S. J. Chapman;D. J. Gavaghan;J. P. Whiteley

  • Verification of computational models of cardiac electro-physiology

    Pras Pathmanathan;Richard A. Gray

  • Uncertainty quantification of fast sodium current steady-state inactivation for multi-scale models of cardiac electrophysiology.

    Pras Pathmanathan;Matthew S. Shotwell;David J. Gavaghan;Jonathan M. Cordeiro

  • Applicability Analysis of Validation Evidence for Biomedical Computational Models

    Pras Pathmanathan;Richard A. Gray;Vicente J. Romero;Tina M. Morrison

  • The significant effect of the choice of ionic current integration method in cardiac electro‐physiological simulations

    Pras Pathmanathan;Gary R. Mirams;James Southern;Jonathan P. Whiteley

  • Ensuring reliability of safety-critical clinical applications of computational cardiac models.

    Pras Pathmanathan;Richard A. Gray

Frequent Co-Authors

Helen M. Byrne
Helen M. Byrne University of Oxford
Philip K. Maini
Philip K. Maini University of Oxford
Oliver E. Jensen
Oliver E. Jensen University of Manchester
Keith Worden
Keith Worden University of Sheffield
Kevin Burrage
Kevin Burrage Queensland University of Technology
Poul M. F. Nielsen
Poul M. F. Nielsen University of Auckland
Bradley J. Roth
Bradley J. Roth Oakland University
Gernot Plank
Gernot Plank Medical University of Graz
Martyn P. Nash
Martyn P. Nash University of Auckland
Peter D. Lee
Peter D. Lee University College London

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