World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
55
Citations
8703
World Ranking
3087
National Ranking
42

Masoud Monjezi 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 Masoud Monjezi 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: 111 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

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

Masoud Monjezi 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 Masoud Monjezi 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: 55 D-Index — 70th percentile

70% of scientists in this discipline score the same or lower.

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

Overview

Masoud Monjezi is affiliated with Tarbiat Modares University in Iran and specializes in the engineering field, with a focus on several subfields including mechanical engineering, civil and structural engineering, mechanics of materials, safety, risk, reliability and quality, and control and systems engineering.

Their primary research interests cover a range of topics related to mineral processing, rock mechanics, and mining technology. Major topics in their work include:

  • Mineral Processing and Grinding
  • Rock Mechanics and Modeling
  • Tunneling and Rock Mechanics
  • Geoscience and Mining Technology
  • Mining Techniques and Economics
  • Tailings Management and Properties
  • Geotechnical Engineering and Analysis

Monjezi's publication record includes numerous articles concentrated in well-regarded journals such as Natural Resources Research, Engineering With Computers, Sustainability, Arabian Journal of Geosciences, and Rock Mechanics and Rock Engineering. The journal Natural Resources Research stands out as the most frequent venue of publication.

Some recent papers authored or coauthored by Monjezi include:

  • A hybrid metaheuristic approach using random forest and particle swarm optimization to study and evaluate backbreak in open-pit blasting, 2022, Neural Computing and Applications
  • Performance of Hybrid SCA-RF and HHO-RF Models for Predicting Backbreak in Open-Pit Mine Blasting Operations, 2021, Natural Resources Research
  • Six Novel Hybrid Extreme Learning Machine-Swarm Intelligence Optimization (ELM-SIO) Models for Predicting Backbreak in Open-Pit Blasting, 2022, Natural Resources Research
  • Prediction of Dust Emission Due to Open Pit Mine Blasting Using a Hybrid Artificial Neural Network, 2021, Natural Resources Research
  • Optimization of blasting design in open pit limestone mines with the aim of reducing ground vibration using robust techniques, 2020, Geomechanics and Geophysics for Geo-Energy and Geo-Resources

The scientist collaborates frequently with several coauthors, reflective of a network in the mining and engineering research community. Frequent collaborators include Manoj Khandelwal, Jian Zhou, Shahab Hosseini, Amin Mousavi, and Danial Jahed Armaghani.

Best Publications

  • Prediction of seismic slope stability through combination of particle swarm optimization and neural network

    Behrouz Gordan;Danial Jahed Armaghani;Mohsen Hajihassani;Masoud Monjezi

  • Feasibility of indirect determination of blast induced ground vibration based on support vector machine

    Mahdi Hasanipanah;Masoud Monjezi;Azam Shahnazar;Danial Jahed Armaghani

  • Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network

    Masoud Monjezi;Mahdi Hasanipanah;Manoj Khandelwal

  • Prediction of blast-induced ground vibration using artificial neural networks

    M. Monjezi;M. Ghafurikalajahi;A. Bahrami

  • Prediction and optimization of back-break and rock fragmentation using an artificial neural network and a bee colony algorithm

    Ebrahim Ebrahimi;Masoud Monjezi;Mohammad Reza Khalesi;Danial Jahed Armaghani

  • Evaluation of effect of blasting pattern parameters on back break using neural networks

    M. Monjezi;H. Dehghani

  • Blast-induced air and ground vibration prediction: a particle swarm optimization-based artificial neural network approach

    Mohsen Hajihassani;Danial Jahed Armaghani;Masoud Monjezi;Edy Tonnizam Mohamad

  • Prediction of the strength and elasticity modulus of granite through an expert artificial neural network

    Danial Jahed Armaghani;Edy Tonnizam Mohamad;Ehsan Momeni;Masoud Monjezi

  • An ANN-based approach to predict blast-induced ground vibration of Gol-E-Gohar iron ore mine,Iran

    Mahdi Saadat;Manoj Khandelwal;M. Monjezi

  • Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

    R Shirani Faradonbeh;D Jahed Armaghani;M. Z. Abd Majid;M. Md Tahir

  • Prediction of flyrock and backbreak in open pit blasting operation: a neuro-genetic approach

    Masoud Monjezi;H. Amini Khoshalan;A. Yazdian Varjani

  • Forecasting blast-induced ground vibration developing a CART model

    Mahdi Hasanipanah;Roohollah Shirani Faradonbeh;Hassan Bakhshandeh Amnieh;Danial Jahed Armaghani

  • A comparative study on the application of various artificial neural networks to simultaneous prediction of rock fragmentation and backbreak

    A. Sayadi;M. Monjezi;N. Talebi;Manoj Khandelwal

  • Development of a fuzzy model to predict flyrock in surface mining

    M. Rezaei;M. Monjezi;A. Yazdian Varjani

  • Prediction of rock fragmentation due to blasting using artificial neural network

    A. Bahrami;M. Monjezi;K. Goshtasbi;A. Ghazvinian

  • Predicting blast-induced ground vibration using various types of neural networks

    M. Monjezi;M. Ahmadi;M. Sheikhan;A. Bahrami

  • Combination of neural network and ant colony optimization algorithms for prediction and optimization of flyrock and back-break induced by blasting

    Amir Saghatforoush;Masoud Monjezi;Roohollah Shirani Faradonbeh;Danial Jahed Armaghani

  • Simultaneous prediction of fragmentation and flyrock in blasting operation using artificial neural networks

    M. Monjezi;A. Bahrami;A. Yazdian Varjani

  • Environmental impact assessment of open pit mining in Iran

    M. Monjezi;K. Shahriar;H. Dehghani;F. Samimi Namin

  • Prediction of rock fragmentation due to blasting in Gol-E-Gohar iron mine using fuzzy logic

    M. Monjezi;M. Rezaei;A. Yazdian Varjani

Frequent Co-Authors

Danial Jahed Armaghani
Danial Jahed Armaghani University of Technology Sydney
Manoj Khandelwal
Manoj Khandelwal Federation University Australia
T. N. Singh
T. N. Singh Indian Institute of Technology Bombay
Mahdi Hasanipanah
Mahdi Hasanipanah Duy Tan University
Edy Tonnizam Mohamad
Edy Tonnizam Mohamad University of Technology Malaysia
Muhd Zaimi Abd Majid
Muhd Zaimi Abd Majid University of Technology Malaysia
Mohsen Hajihassani
Mohsen Hajihassani Urmia University
Aminaton Marto
Aminaton Marto University of Technology Malaysia
Diyuan Li
Diyuan Li Central South University
Raoof Gholami
Raoof Gholami University of Stavanger

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