World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
46
Citations
8543
World Ranking
5139
National Ranking
1461

Shawn C. Shadden 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 Shawn C. Shadden 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: 161 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

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

Shawn C. Shadden 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 Shawn C. Shadden 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: 46 D-Index — 49th percentile

49% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2014 - Hellman Fellow

Overview

Shawn C. Shadden is affiliated with the University of California, Berkeley in the United States. Their research spans several areas primarily at the intersection of medicine and engineering, with a strong focus on cardiovascular and biomedical applications.

The main fields of study for Shadden include Medicine and Engineering. Within these broad areas, they have contributed notably to subfields such as Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Computational Mechanics, and Surgery.

Their research covers a diverse range of topics, including:

  • 3D Shape Modeling and Analysis
  • Cardiovascular Function and Risk Factors
  • Elasticity and Material Modeling
  • Coronary Interventions and Diagnostics
  • Medical Image Segmentation Techniques
  • Advanced Neuroimaging Techniques and Applications
  • Cardiovascular Health and Disease Prevention

Shadden has published in several frequent venues, such as:

  • arXiv (Cornell University)
  • Journal of Biomechanical Engineering
  • Annals of Biomedical Engineering
  • Journal of Biomechanics
  • Medical Image Analysis

Their recent papers include:

  • "A deep-learning approach for direct whole-heart mesh reconstruction" (2021), Medical Image Analysis
  • "Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge" (2021), Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona)
  • "Machine Learning for Cardiovascular Biomechanics Modeling: Challenges and Beyond" (2022), Annals of Biomedical Engineering
  • "A Distributed Lumped Parameter Model of Blood Flow" (2020), Annals of Biomedical Engineering
  • "svFSI: A Multiphysics Package for Integrated CardiacModeling" (2022), The Journal of Open Source Software

Frequent co-authors that have collaborated with Shadden include:

  • Fanwei Kong
  • Siavash Ameli
  • Nathan M. Wilson
  • Mehran Mirramezani
  • Dave Parker

Among awards, Shadden received the Hellman Fellowship in 2014.

Best Publications

  • Definition and properties of Lagrangian coherent structures from finite-time Lyapunov exponents in two-dimensional aperiodic flows

    Shawn C. Shadden;Francois Lekien;Jerrold E. Marsden

  • SimVascular: An Open Source Pipeline for Cardiovascular Simulation

    Adam Updegrove;Nathan M. Wilson;Jameson Merkow;Hongzhi Lan

  • Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge.

    Víctor M. Campello;Polyxeni Gkontra;Cristian Izquierdo;Carlos Martín-Isla

  • Quantification of Hemodynamics in Abdominal Aortic Aneurysms During Rest and Exercise Using Magnetic Resonance Imaging and Computational Fluid Dynamics

    Andrea S. Les;Shawn C. Shadden;C. Alberto Figueroa;Jinha M. Park

  • Lagrangian analysis of fluid transport in empirical vortex ring flows

    Shawn C. Shadden;John O. Dabiri;Jerrold E. Marsden

  • Collision avoidance for multiple agent systems

    D.E. Chang;S.C. Shadden;J.E. Marsden;R. Olfati-Saber

  • Lagrangian coherent structures in n-dimensional systems

    Francois Lekien;Shawn C. Shadden;Jerrold E. Marsden

  • Evaluation of a novel Y-shaped extracardiac Fontan baffle using computational fluid dynamics.

    Alison L. Marsden;Adam J. Bernstein;V. Mohan Reddy;Shawn C. Shadden

  • Characterization of Coherent Structures in the Cardiovascular System

    Shawn C. Shadden;Charles A. Taylor

  • Variability of computational fluid dynamics solutions for pressure and flow in a giant aneurysm: the ASME 2012 Summer Bioengineering Conference CFD Challenge.

    David A. Steinman;Yiemeng Hoi;Paul Fahy;Liam Morris

  • Study of blood flow impact on growth of thrombi using a multiscale model

    Zhiliang Xu;Nan Chen;Shawn C. Shadden;Jerrold E. Marsden

  • Optimal trajectory generation in ocean flows

    T. Inanc;S.C. Shadden;J.E. Marsden

  • The correlation between surface drifters and coherent structures based on high-frequency radar data in Monterey Bay

    Shawn S.C. Shadden;Francois Lekien;Jeffrey J.D. Paduan;Francisco F.P. Chavez

  • Image-based modeling of hemodynamics in coronary artery aneurysms caused by Kawasaki disease.

    Dibyendu Sengupta;Andrew M. Kahn;Jane C. Burns;Jane C. Burns;Sethuraman Sankaran

  • Computational analysis of an aortic valve jet with Lagrangian coherent structures.

    Shawn C. Shadden;Matteo Astorino;Jean-Frédéric Gerbeau

  • Transport and stirring induced by vortex formation

    S. C. Shadden;K. Katija;M. Rosenfeld;J. E. Marsden

  • Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge

    Kristian Valen-Sendstad;Aslak W. Bergersen;Aslak W. Bergersen;Yuji Shimogonya;Leonid Goubergrits

  • A longitudinal comparison of hemodynamics and intraluminal thrombus deposition in abdominal aortic aneurysms

    Amirhossein Arzani;Ga-Young Suh;Ronald L. Dalman;Shawn C. Shadden

  • Characterizations and Correlations of Wall Shear Stress in Aneurysmal Flow

    Amirhossein Arzani;Shawn C. Shadden

  • Lagrangian Coherent Structures

    Shawn C. Shadden

  • Quantification of Particle Residence Time in Abdominal Aortic Aneurysms Using Magnetic Resonance Imaging and Computational Fluid Dynamics

    Ga-Young Suh;Andrea S. Les;Adam S. Tenforde;Shawn C. Shadden

Frequent Co-Authors

Alison L. Marsden
Alison L. Marsden Stanford University
Jerrold E. Marsden
Jerrold E. Marsden California Institute of Technology
Xiao Hu
Xiao Hu University of Hong Kong
Ronald L. Dalman
Ronald L. Dalman Stanford University
Robert J. Herfkens
Robert J. Herfkens Stanford University
John O. Dabiri
John O. Dabiri California Institute of Technology
Jean-Frédéric Gerbeau
Jean-Frédéric Gerbeau French Institute for Research in Computer Science and Automation - INRIA
David A. Steinman
David A. Steinman University of Toronto
Andrew J. Szeri
Andrew J. Szeri University of California, Berkeley
Scott L. Diamond
Scott L. Diamond University of Pennsylvania

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