World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
51
Citations
12908
World Ranking
3784
National Ranking
1109

Habib N. Najm 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 Habib N. Najm 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: 356 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Habib N. Najm 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 Habib N. Najm 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: 51 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Habib N. Najm is affiliated with Sandia National Laboratories in the United States. Their research spans multiple fields, primarily concentrating on engineering and materials science. Within these areas, their work extensively covers materials chemistry and incorporates significant investigations in artificial intelligence and aerospace engineering.

The scientist has contributed to key topics including machine learning applications in materials science, advanced combustion engine technologies, neural networks, chemical physics studies, combustion and flame dynamics, as well as nuclear reactor physics and nuclear materials properties.

Frequent publication venues featuring their work include:

  • arXiv (Cornell University)
  • The Journal of Physical Chemistry A
  • Computational Materials Science
  • Combustion Theory and Modelling
  • Combustion and Flame

Recent papers authored or co-authored by Habib N. Najm demonstrate engagement with interdisciplinary research topics. Notable publications include:

  • "2022 Review of Data-Driven Plasma Science," 2023, IEEE Transactions on Plasma Science
  • "The origin of CEMA and its relation to CSP," 2021, Combustion and Flame
  • "Automated Reaction Kinetics of Gas-Phase Organic Species over Multiwell Potential Energy Surfaces," 2023, The Journal of Physical Chemistry A
  • "Sella, an Open-Source Automation-Friendly Molecular Saddle Point Optimizer," 2022, Journal of Chemical Theory and Computation
  • "Geometry optimization speedup through a geodesic approach to internal coordinates," 2021, The Journal of Chemical Physics

Collaborations constitute an important component of their scientific output. Frequent co-authors include Khachik Sargsyan, Judit Zádor, Cosmin Safta, Tiernan Casey, and Pieterjan Robbe.

Best Publications

  • Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics

    Habib N. Najm

  • On the Adequacy of Certain Experimental Observables as Measurements of Flame Burning Rate

    Habib N Najm;Phillip H Paul;Charles J Mueller;Peter S Wyckoff

  • Numerical Challenges in the Use of Polynomial Chaos Representations for Stochastic Processes

    Bert J. Debusschere;Habib N. Najm;Philippe P. Pébay;Omar M. Knio

  • Stochastic spectral methods for efficient Bayesian solution of inverse problems

    Youssef M. Marzouk;Habib N. Najm;Larry A. Rahn

  • Uncertainty propagation using Wiener-Haar expansions

    O. P. Le Maître;O. M. Knio;H. N. Najm;R. G. Ghanem

  • A stochastic projection method for fluid flow. I: basic formulation

    Olivier P. Le Maitre;Omar M. Kino;Habib N. Najm;Roger G. Ghanem

  • Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems

    Youssef M. Marzouk;Habib N. Najm

  • A stochastic projection method for fluid flow II.: random process

    Olivier P. Le Maîetre;Matthew T. Reagan;Habib N. Najm;Roger G. Ghanem

  • Multi-resolution analysis of wiener-type uncertainty propagation schemes

    O. P. Le Maître;H. N. Najm;R. G. Ghanem;O. M. Knio

  • Uncertainty quantification in reacting-flow simulations through non-intrusive spectral projection

    Matthew T. Reagan;Habib N. Najm;Roger G. Ghanem;Omar M. Knio

  • Planar laser-induced fluorescence imaging of flame heat release rate

    Phillip H. Paul;Habib N. Najm

  • A Semi-implicit Numerical Scheme for Reacting Flow

    Habib N. Najm;Peter S. Wyckoff;Omar M. Knio

  • An automatic procedure for the simplification of chemical kinetic mechanisms based on CSP

    Mauro Valorani;Francesco Creta;Dimitris A. Goussis;Jeremiah C. Lee

  • Workshop Report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence

    Nathan Baker;Frank Alexander;Timo Bremer;Aric Hagberg

  • CSP analysis of a transient flame-vortex interaction: time scales and manifolds

    Mauro Valorani;Habib N. Najm;Dimitris A. Goussis

  • DIMENSIONALITY REDUCTION FOR COMPLEX MODELS VIA BAYESIAN COMPRESSIVE SENSING

    Khachik Sargsyan;Cosmin Safta;Habib N. Najm;Bert J. Debusschere

  • Uncertainty quantification in chemical systems

    Habib N. Najm;Bert Debusschere;Youssef Marzouk;S. Widmer

  • Regular Article: A Semi-implicit Numerical Scheme for Reacting Flow

    Omar M Knio;Habib N Najm;Peter S Wyckoff

  • On the Statistical Calibration of Physical Models

    K. Sargsyan;H. N. Najm;R. Ghanem

  • A Study of Flame Observables in Premixed Methane - Air Flames

    H. N. Najm;O. M. Knio;P. H. Paul;P.S. Wyckoff

  • Multi-point pyrometry with real-time surface emissivity compensation

    Mehrdad M. Moslehi;Habib N. Najm

Frequent Co-Authors

Omar M. Knio
Omar M. Knio King Abdullah University of Science and Technology
Dimitris A. Goussis
Dimitris A. Goussis Khalifa University
Roger Ghanem
Roger Ghanem University of Southern California
Michael Frenklach
Michael Frenklach University of California, Berkeley
Joseph C. Oefelein
Joseph C. Oefelein Georgia Institute of Technology
Ali Pinar
Ali Pinar Sandia National Laboratories
Jean-Paul Watson
Jean-Paul Watson Lawrence Livermore National Laboratory

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