World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
53
Citations
9632
World Ranking
3449
National Ranking
144

Nima Khakzad 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 Nima Khakzad 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: 156 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Nima Khakzad 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 Nima Khakzad 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: 53 D-Index — 66th percentile

66% of scientists in this discipline score the same or lower.

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

Overview

Nima Khakzad is a researcher affiliated with Toronto Metropolitan University in Canada. Their work primarily focuses on areas intersecting decision sciences, engineering, and health professions, with significant contributions to the fields of statistics, probability and uncertainty, radiological and ultrasound technology, aerospace engineering, safety, risk, reliability and quality, as well as civil and structural engineering.

The scientist's research topics commonly include:

  • Risk and Safety Analysis
  • Occupational Health and Safety Research
  • Combustion and Detonation Processes
  • Reliability and Maintenance Optimization
  • Infrastructure Resilience and Vulnerability Analysis
  • Fault Detection and Control Systems
  • Structural Integrity and Reliability Analysis

Khakzad's frequent publication venues demonstrate an emphasis on reliability and safety within engineering contexts:

  • Reliability Engineering & System Safety
  • Journal of Loss Prevention in the Process Industries
  • The Canadian Journal of Chemical Engineering
  • Safety Science
  • Process Safety Progress

Frequent co-authors collaborating with Khakzad include:

  • Genserik Reniers
  • Gabriele Landucci
  • Chao Chen
  • Ming Yang
  • Faisal Khan

Some of Khakzad's recent publications include:

  • A thorough classification and discussion of approaches for modeling and managing domino effects in the process industries, 2020, Safety Science
  • Quantitative resilience assessment of chemical process systems using functional resonance analysis method and Dynamic Bayesian network, 2020, Reliability Engineering & System Safety
  • An Integrated Quantitative Risk Assessment Method for Urban Underground Utility Tunnels, 2021, Reliability Engineering & System Safety
  • A dynamic multi-agent approach for modeling the evolution of multi-hazard accident scenarios in chemical plants, 2020, Reliability Engineering & System Safety
  • Dynamic vulnerability assessment of process plants with respect to vapor cloud explosions, 2020, Reliability Engineering & System Safety

Best Publications

  • Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches

    Nima Khakzad;Faisal I. Khan;Paul Amyotte

  • Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network

    Nima Khakzad;Faisal Khan;Paul Amyotte

  • Quantitative risk analysis of offshore drilling operations: A Bayesian approach

    Nima Khakzad;Faisal Khan;Paul Amyotte

  • Dynamic risk analysis using bow-tie approach

    Nima Khakzad;Faisal I. Khan;Paul Amyotte

  • Application of dynamic Bayesian network to risk analysis of domino effects in chemical infrastructures

    Nima Khakzad

  • Domino effect analysis using Bayesian networks.

    Nima Khakzad;Faisal Khan;Paul Amyotte;Valerio Cozzani

  • Dynamic safety assessment of natural gas stations using Bayesian network.

    Esmaeil Zarei;Ali Azadeh;Nima Khakzad;Mostafa Mirzaei Aliabadi

  • Dust explosions: A threat to the process industries

    Zhi Yuan;Nima Khakzad;Nima Khakzad;Faisal Khan;Paul Amyotte

  • Dynamic safety risk analysis of offshore drilling

    Majeed Abimbola;Faisal Khan;Nima Khakzad

  • Safety analysis of process systems using Fuzzy Bayesian Network (FBN)

    Esmaeil Zarei;Nima Khakzad;Valerio Cozzani;Genserik Reniers;Genserik Reniers

  • Safety and risk analysis of managed pressure drilling operation using Bayesian network

    Majeed Abimbola;Faisal Khan;Nima Khakzad;Stephen Butt

  • The role of human error in risk analysis: Application to pre- and post-maintenance procedures of process facilities

    Alireza Noroozi;Nima Khakzad;Faisal I. Khan;Scott N. MacKinnon

  • Risk-based design of process systems using discrete-time Bayesian networks

    Nima Khakzad;Faisal I. Khan;Paul Amyotte

  • Validity and validation of safety-related quantitative risk analysis: A review

    Floris Goerlandt;Floris Goerlandt;Nima Khakzad;Genserik Reniers;Genserik Reniers;Genserik Reniers

  • On the application of near accident data to risk analysis of major accidents

    Nima Khakzad;Faisal I. Khan;Faisal I. Khan;Nicola Paltrinieri

  • Application of dynamic Bayesian network to performance assessment of fire protection systems during domino effects

    Nima Khakzad;Gabriele Landucci;Genserik Reniers;Genserik Reniers

  • Using graph theory to analyze the vulnerability of process plants in the context of cascading effects

    Nima Khakzad;Genserik Reniers;Genserik Reniers;Genserik Reniers

  • Integrating safety and security resources to protect chemical industrial parks from man-made domino effects: A dynamic graph approach

    Chao Chen;Genserik Reniers;Genserik Reniers;Genserik Reniers;Nima Khakzad

  • A thorough classification and discussion of approaches for modeling and managing domino effects in the process industries

    Chao Chen;Genserik Reniers;Genserik Reniers;Genserik Reniers;Nima Khakzad

  • Risk analysis of dust explosion scenarios using Bayesian networks.

    Zhi Yuan;Nima Khakzad;Faisal Khan;Paul Amyotte

Frequent Co-Authors

Genserik Reniers
Genserik Reniers Delft University of Technology
Faisal Khan
Faisal Khan Texas A&M University
Valerio Cozzani
Valerio Cozzani University of Bologna
Gabriele Landucci
Gabriele Landucci University of Pisa
Paul Amyotte
Paul Amyotte Dalhousie University
Rouzbeh Abbassi
Rouzbeh Abbassi Macquarie University
Floris Goerlandt
Floris Goerlandt Dalhousie University
Ali Azadeh
Ali Azadeh University of Tehran
Biswajeet Pradhan
Biswajeet Pradhan University of Technology Sydney
Ernesto Salzano
Ernesto Salzano University of Bologna

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