World's Best Scientists 2026 revealed!
Majidreza Nazem

Majidreza Nazem

D-Index & Metrics

Engineering and Technology

D-Index
32
Citations
3794
World Ranking
9597
National Ranking
464

Majidreza Nazem 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 Majidreza Nazem 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: 119 publications — 15th percentile

15% of scientists in this discipline score the same or lower.

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

Majidreza Nazem 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 Majidreza Nazem 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

Majidreza Nazem is a researcher affiliated with RMIT University in Australia, specializing primarily in the field of engineering. Their work focuses on multiple subfields within this area, including Civil and Structural Engineering, Safety, Risk, Reliability and Quality, Management, Monitoring, Policy and Law, Artificial Intelligence, and Ocean Engineering.

The core topics addressed in their research include Geotechnical Engineering and Analysis, Landslides and Related Hazards, Soil and Unsaturated Flow, Geotechnical Engineering and Soil Stabilization, Geotechnical Engineering and Underground Structures, Geotechnical Engineering and Soil Mechanics, and Dam Engineering and Safety.

They have contributed to the academic community through multiple publications, with a significant presence in journals such as Computers and Geotechnics, Acta Geotechnica, Engineering With Computers, SSRN Electronic Journal, and the Journal of Rock Mechanics and Geotechnical Engineering. These venues host the majority of their research outputs.

Recent publications authored or co-authored by Majidreza Nazem include:

  • Improved prediction of slope stability using a hybrid stacking ensemble method based on finite element analysis and field data (2020, Journal of Rock Mechanics and Geotechnical Engineering)
  • A novel technique based on the improved firefly algorithm coupled with extreme learning machine (ELM-IFF) for predicting the thermal conductivity of soil (2021, Engineering With Computers)
  • Predicting the thermal conductivity of soils using integrated approach of ANN and PSO with adaptive and time-varying acceleration coefficients (2021, International Journal of Thermal Sciences)
  • Modelling of municipal solid waste gasification using an optimised ensemble soft computing model (2020, Fuel)
  • Prediction of the resilient modulus of compacted subgrade soils using ensemble machine learning methods (2022, Transportation Geotechnics)

The researcher has collaborated frequently with other scientists, including:

  • Annan Zhou
  • Navid Kardani
  • Mohammad Aminpour
  • Sara Moridpour
  • Javad Ghorbani

Best Publications

  • Large deformation finite element analyses in geotechnical engineering

    Dong Wang;Britta Bienen;Majid Nazem;Yinghui Tian

  • Improved prediction of slope stability using a hybrid stacking ensemble method based on finite element analysis and field data

    Navid Kardani;Annan Zhou;Majidreza Nazem;Shui-Long Shen;Shui-Long Shen

  • Numerical analysis of a large landslide induced by coal mining subsidence

    E. Fathi Salmi;M. Nazem;M. Karakus

  • Stress integration and mesh refinement for large deformation in geomechanics

    Majidreza Nazem;Daichao Sheng;John P. Carter

  • Arbitrary Lagrangian-Eulerian method for large-strain consolidation problems

    Majidreza Nazem;Daichao Sheng;John P. Carter;Scott W. Sloan

  • The effect of rock mass gradual deterioration on the mechanism of post-mining subsidence over shallow abandoned coal mines

    Ebrahim Fathi Salmi;Majidreza Nazem;Murat Karakus

  • Predicting the thermal conductivity of soils using integrated approach of ANN and PSO with adaptive and time-varying acceleration coefficients

    Unknown

  • Estimation of Bearing Capacity of Piles in Cohesionless Soil Using Optimised Machine Learning Approaches

    Navid Kardani;Annan Zhou;Majidreza Nazem;Shui-Long Shen;Shui-Long Shen

  • A novel technique based on the improved firefly algorithm coupled with extreme learning machine (ELM-IFF) for predicting the thermal conductivity of soil

    Navid Kardani;Abidhan Bardhan;Pijush Samui;Majidreza Nazem

  • Arbitrary Lagrangian–Eulerian method for dynamic analysis of geotechnical problems

    Majidreza Nazem;John P Carter;David W Airey

  • Some computational aspects for solving deep penetration problems in geomechanics

    Daichao Sheng;Majidreza Nazem;John P. Carter

  • Dynamic analysis of a smooth penetrometer free falling into uniform clay

    M. Nazem;J.P. Carter;D.W. Airey;Shiaohuey Chow

  • Application of the distinct element method and the extended finite element method in modelling cracks and coalescence in brittle materials

    M. Sharafisafa;M. Nazem

  • Prediction of the resilient modulus of compacted subgrade soils using ensemble machine learning methods

    Unknown

  • Modelling of municipal solid waste gasification using an optimised ensemble soft computing model

    Navid Kardani;Annan Zhou;Majidreza Nazem;Xiaoshan Lin

  • Large deformation dynamic analysis of saturated porous media with applications to penetration problems

    H. Sabetamal;M. Nazem;J.P. Carter;S.W. Sloan

  • Predicting permeability of tight carbonates using a hybrid machine learning approach of modified equilibrium optimizer and extreme learning machine

    Navid Kardani;Abidhan Bardhan;Shubham Gupta;Pijush Samui

  • A review on existing sensors and devices for inspecting railway infrastructure

    Amir Falamarzi;Sara Moridpour;Majidreza Nazem

  • Expanded polystyrene geofoam in pavement construction

    Abbas Mohajerani;Matthew Ashdown;Luqmaan Abdihashi;Majidreza Nazem

  • Numerical modelling of multiphase flow in unsaturated deforming porous media

    Javad Ghorbani;Majidreza Nazem;John Carter

  • A novel improved Harris Hawks optimization algorithm coupled with ELM for predicting permeability of tight carbonates

    Navid Kardani;Abidhan Bardhan;Bishwajit Roy;Pijush Samui

  • Estimating unconfined compressive strength of unsaturated cemented soils using alternative evolutionary approaches

    Navid Kardani;Annan Zhou;Shui-Long Shen;Majidreza Nazem

Frequent Co-Authors

John P. Carter
John P. Carter University of Newcastle Australia
Scott W. Sloan
Scott W. Sloan University of Newcastle Australia
Annan Zhou
Annan Zhou RMIT University
Daichao Sheng
Daichao Sheng University of Technology Sydney
Shui-Long Shen
Shui-Long Shen Shantou University
Pijush Samui
Pijush Samui National Institute of Technology Patna
Murat Karakus
Murat Karakus University of Adelaide
Mark Cassidy
Mark Cassidy University of Melbourne
Mark Randolph
Mark Randolph University of Western Australia
Danial Jahed Armaghani
Danial Jahed Armaghani University of Technology Sydney

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