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Danial Jahed Armaghani
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Rising Stars
2025
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Engineering and Technology
Malaysia
2022

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Rising Stars 85 15 15 2 2 246 18680
Engineering and Technology 91 255 242 19 19 246 21470

Danial Jahed Armaghani publications per year

The chart shows the history of publications by Danial Jahed Armaghani between 2012 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Danial Jahed Armaghani published across 15 years, from 2012 to 2026, averaging 25.5 papers a year. Output peaked at 58 publications in 2021. 34 of the 383 publications appeared in the last two years.

No. of publications
10 20 30 40 50
Bar chart. Horizontal axis: year, 2012 to 2026. Vertical axis: number of publications, 0 to 58. Peak 58 publications in 2021. 2012: 2 publications 2013: 6 publications 2014: 2 publications 2015: 19 publications 2016: 26 publications 2017: 16 publications 2018: 18 publications 2019: 23 publications 2020: 51 publications 2021: 58 publications 2022: 47 publications 2023: 34 publications 2024: 47 publications 2025: 31 publications 2026: 3 publications
2012 2026

383 publications in total across all disciplines

View publications per year as a table
Danial Jahed Armaghani: publications per year, 2012 to 2026
Year Publications
2012 2
2013 6
2014 2
2015 19
2016 26
2017 16
2018 18
2019 23
2020 51
2021 58
2022 47
2023 34
2024 47
2025 31
2026 3
Total 383
Download as CSV

Danial Jahed Armaghani 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 Danial Jahed Armaghani sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: publications, 38–47 to 804+. Vertical axis: number of scientists, 0 to 457. Most scientists, 457, have 148–157 publications. The last bar groups every scientist with 804 publications or more. The highlighted bar, 238–247 publications, is where this scientist sits. 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
38–47 publications 804+

This scientist: 246 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications Scientists This scientist
38–47 20
48–57 35
58–67 96
68–77 135
78–87 190
88–97 259
98–107 283
108–117 369
118–127 341
128–137 386
138–147 372
148–157 457
158–167 415
168–177 407
178–187 421
188–197 378
198–207 403
208–217 317
218–227 346
228–237 321
238–247 260 246
248–257 280
258–267 240
268–277 214
278–287 242
288–297 203
298–307 166
308–317 154
318–327 175
328–337 159
338–347 99
348–357 131
358–367 106
368–377 118
378–387 97
388–397 108
398–407 82
408–417 71
418–427 64
428–437 55
438–447 54
448–457 60
458–467 47
468–477 40
478–487 30
488–497 29
498–507 38
508–517 40
518–527 32
528–537 23
538–547 28
548–557 23
558–567 19
568–577 16
578–587 17
588–597 18
598–607 22
608–617 15
618–627 9
628–637 11
638–647 21
648–657 12
658–667 9
668–677 11
678–687 9
688–697 6
698–707 14
708–717 7
718–727 8
728–737 10
738–747 9
748–757 5
758–767 5
768–777 11
778–787 7
788–797 2
798–803 4
804+ 100
Download as CSV

Danial Jahed Armaghani 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 Danial Jahed Armaghani sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: D-Index, 30 to 107+. Vertical axis: number of scientists, 0 to 426. Most scientists, 426, have 42 D-Index. The last bar groups every scientist with 107 D-Index or more. The highlighted bar, 91 D-Index, is where this scientist sits. 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: 91 D-Index — 98th percentile

98% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index Scientists This scientist
30 59
31 114
32 129
33 189
34 200
35 262
36 311
37 312
38 350
39 385
40 348
41 362
42 426
43 380
44 310
45 341
46 301
47 306
48 271
49 246
50 210
51 253
52 213
53 221
54 195
55 186
56 170
57 167
58 166
59 144
60 152
61 141
62 138
63 131
64 118
65 114
66 119
67 95
68 87
69 77
70 89
71 69
72 54
73 46
74 55
75 54
76 49
77 53
78 46
79 28
80 39
81 36
82 24
83 26
84 36
85 18
86 25
87 19
88 26
89 27
90 23
91 15 91
92 12
93 9
94 15
95 10
96 13
97 13
98 9
99 7
100 7
101 8
102 7
103 7
104 9
105 6
106 9
107+ 99
Download as CSV

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award
  • 2022 - Research.com Engineering and Technology in Malaysia Leader Award

Overview

Danial Jahed Armaghani is affiliated with the University of Technology Sydney in Australia. Their research primarily focuses on the field of engineering, with a specialization in civil and structural engineering. Their work extends to several subfields, including mechanics of materials, mechanical engineering, ocean engineering, and safety, risk, reliability, and quality.

The scientist's main research topics include rock mechanics and modeling, tunneling and rock mechanics, mineral processing and grinding, drilling and well engineering, geotechnical engineering and analysis, landslides and related hazards, and dam engineering and safety.

Frequent coauthors collaborating with Danial Jahed Armaghani include Panagiotis G. Asteris, Jian Zhou, Edy Tonnizam Mohamad, Mohammadreza Koopialipoor, and Ahmed Salih Mohammed.

They have published extensively in several venues such as Applied Sciences, Engineering With Computers, Natural Resources Research, Transportation Geotechnics, and Sustainability.

Notable recent papers include:

  • A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength (2020) published in Neural Computing and Applications
  • Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate (2020) published in Engineering Applications of Artificial Intelligence
  • Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques (2020) published in Geoscience Frontiers
  • Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization (2020) published in Underground Space
  • Prediction of cement-based mortars compressive strength using machine learning techniques (2021) published in Neural Computing and Applications

They have contributed to book publications through publishers such as Springer Nature and Emerging Trends in Mechatronics. Titles include "Applications of Artificial Intelligence in Tunnelling and Underground Space Technology" (2021), "Environmental Issues of Blasting" (2021), and "Artificial Intelligence in Mechatronics and Civil Engineering" (2023).

Best Publications

  • Development of hybrid intelligent models for predicting TBM penetration rate in hard rock condition

    Danial Jahed Armaghani;Edy Tonnizam Mohamad;Mogana Sundaram Narayanasamy;Nobuya Narita

  • A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength

    Danial Jahed Armaghani;Panagiotis G. Asteris

  • Prediction of uniaxial compressive strength of rock samples using hybrid particle swarm optimization-based artificial neural networks

    Ehsan Momeni;Danial Jahed Armaghani;Mohsen Hajihassani;Mohd For Mohd Amin

  • 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

  • Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate

    Jian Zhou;Yingui Qiu;Shuangli Zhu;Danial Jahed Armaghani

  • Ground vibration prediction in quarry blasting through an artificial neural network optimized by imperialist competitive algorithm

    Mohsen Hajihassani;Danial Jahed Armaghani;Aminaton Marto;Edy Tonnizam Mohamad

  • Feasibility of PSO-ANN model for predicting surface settlement caused by tunneling

    Mahdi Hasanipanah;Majid Noorian-Bidgoli;Danial Jahed Armaghani;Hossein Khamesi

  • Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns

    Payam Sarir;Jun Chen;Panagiotis G. Asteris;Danial Jahed Armaghani

  • Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

    Jian Zhou;Yingui Qiu;Danial Jahed Armaghani;Wengang Zhang

  • Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization

    Jian Zhou;Yingui Qiu;Shuangli Zhu;Danial Jahed Armaghani

  • Prediction of cement-based mortars compressive strength using machine learning techniques

    Panagiotis G. Asteris;Mohammadreza Koopialipoor;Danial Jahed Armaghani;Evgenios A. Kotsonis

  • Prediction of the unconfined compressive strength of soft rocks: a PSO-based ANN approach

    Edy Tonnizam Mohamad;Danial Jahed Armaghani;Ehsan Momeni;Seyed Vahid Alavi Nezhad Khalil Abad

  • 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

  • Application of several optimization techniques for estimating TBM advance rate in granitic rocks

    Danial Jahed Armaghani;Mohammadreza Koopialipoor;Aminaton Marto;Saffet Yagiz

  • Random Forests and Cubist Algorithms for Predicting Shear Strengths of Rockfill Materials

    Jian Zhou;Enming Li;Haixia Wei;Chuanqi Li

  • Prediction of ground vibration induced by blasting operations through the use of the Bayesian Network and random forest models

    Jian Zhou;Panagiotis G. Asteris;Danial Jahed Armaghani;Binh Thai Pham

  • Supervised machine learning techniques to the prediction of tunnel boring machine penetration rate

    Hai Xu;Jian Zhou;Panagiotis G. Asteris;Danial Jahed Armaghani

  • Applying various hybrid intelligent systems to evaluate and predict slope stability under static and dynamic conditions

    Mohammadreza Koopialipoor;Danial Jahed Armaghani;Danial Jahed Armaghani;Ahmadreza Hedayat;Aminaton Marto

  • Developing a hybrid PSO---ANN model for estimating the ultimate bearing capacity of rock-socketed piles

    Danial Jahed Armaghani;Raja Shahrom Shoib;Koohyar Faizi;Ahmad Safuan Rashid

  • 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

  • An adaptive neuro-fuzzy inference system for predicting unconfined compressive strength and Young’s modulus: a study on Main Range granite

    Danial Jahed Armaghani;Edy Tonnizam Mohamad;Ehsan Momeni;Mogana Sundaram Narayanasamy

Frequent Co-Authors

Edy Tonnizam Mohamad
Edy Tonnizam Mohamad University of Technology Malaysia
Mohammadreza Koopialipoor
Mohammadreza Koopialipoor Amirkabir University of Technology
Mahdi Hasanipanah
Mahdi Hasanipanah Duy Tan University
Masoud Monjezi
Masoud Monjezi Tarbiat Modares University
Panagiotis G. Asteris
Panagiotis G. Asteris School of Pedagogical and Technological Education
Mahmood Md. Tahir
Mahmood Md. Tahir University of Technology Malaysia
Aminaton Marto
Aminaton Marto University of Technology Malaysia
Manoj Khandelwal
Manoj Khandelwal Federation University Australia
Mohsen Hajihassani
Mohsen Hajihassani Urmia University
Muhd Zaimi Abd Majid
Muhd Zaimi Abd Majid University of Technology Malaysia

External Links

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Best Scientists Citing Danial Jahed Armaghani

Hossein Moayedi

Hossein Moayedi

Duy Tan University

Publications: 48

Mahdi Hasanipanah

Mahdi Hasanipanah

Duy Tan University

Publications: 45

Dieu Tien Bui

Dieu Tien Bui

University of South-Eastern Norway

Publications: 25

Ahmad Safuan A. Rashid

Ahmad Safuan A. Rashid

University of Technology Malaysia

Publications: 17

Chongchong Qi

Chongchong Qi

Central South University

Publications: 16

Trung Nguyen-Thoi

Trung Nguyen-Thoi

Van Lang University

Publications: 13

Panagiotis G. Asteris

Panagiotis G. Asteris

School of Pedagogical and Technological Education

Publications: 13

Manoj Khandelwal

Manoj Khandelwal

Federation University Australia

Publications: 12

Mahmood Md. Tahir

Mahmood Md. Tahir

University of Technology Malaysia

Publications: 10

Zaher Mundher Yaseen

Zaher Mundher Yaseen

King Fahd University of Petroleum and Minerals

Publications: 9

Mohammadreza Koopialipoor

Mohammadreza Koopialipoor

Amirkabir University of Technology

Publications: 9

T. N. Singh

T. N. Singh

Indian Institute of Technology Bombay

Publications: 9

Pijush Samui

Pijush Samui

National Institute of Technology Patna

Publications: 9

Masoud Monjezi

Masoud Monjezi

Tarbiat Modares University

Publications: 8

Mohsen Hajihassani

Mohsen Hajihassani

Urmia University

Publications: 8

Yudong Zhang

Yudong Zhang

University of Leicester

Publications: 8

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