World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
50
Citations
7398
World Ranking
4176
National Ranking
835

Chongchong Qi 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 Chongchong Qi 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: 141 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Chongchong Qi 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 Chongchong Qi 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: 50 D-Index — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Overview

Chongchong Qi is affiliated with Central South University in China and has contributed to research primarily within the fields of Engineering and Environmental Science. Their work spans several subfields, including Civil and Structural Engineering, Mechanical Engineering, Building and Construction, Artificial Intelligence, and Mechanics of Materials.

The primary topics addressed in Qi's research focus on various aspects related to mineral processing, geochemistry, and environmental considerations in engineering contexts. These topics include:

  • Mineral Processing and Grinding
  • Tailings Management and Properties
  • Geochemistry and Geologic Mapping
  • Concrete and Cement Materials Research
  • Rock Mechanics and Modeling
  • Coal and Its By-products
  • Mine drainage and remediation techniques

Qi's recent publications reflect an engagement with data-driven and computational methods in geotechnical and environmental engineering. Notable papers include:

  • "A spatially explicit deep learning neural network model for the prediction of landslide susceptibility," 2020, published in CATENA
  • "Big data management in the mining industry," 2020, published in International Journal of Minerals Metallurgy and Materials
  • "Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping," 2020, published in CATENA
  • "Permeability prediction of porous media using a combination of computational fluid dynamics and hybrid machine learning methods," 2020, published in Engineering With Computers
  • "Co-disposal of magnesium slag and high-calcium fly ash as cementitious materials in backfill," 2020, published in Journal of Cleaner Production

The researcher collaborates frequently with several co-authors, including Qiusong Chen, Mengting Wu, Qinli Zhang, Xinhang Xu, and Tao Hu. These collaborations indicate a networked research approach within the relevant engineering and materials science communities.

Qi's work is published in a variety of academic venues, indicating a multidisciplinary interest. The most frequent publication venues are:

  • International Journal of Minerals Metallurgy and Materials
  • Construction and Building Materials
  • SSRN Electronic Journal
  • Environmental Research
  • Journal of Cleaner Production

Across these contributions, Chongchong Qi's research employs modern analytical techniques including machine learning, computational fluid dynamics, and big data management. The focus on material properties, environmental impacts of mining, and engineering applications situates the researcher within applied science disciplines addressing industrial and environmental challenges.

Best Publications

  • Cemented paste backfill for mineral tailings management: Review and future perspectives

    Chongchong Qi;Andy Fourie

  • Recycling phosphogypsum and construction demolition waste for cemented paste backfill and its environmental impact

    Qiusong Chen;Qiusong Chen;Qinli Zhang;Chongchong Qi;Andy Fourie

  • A spatially explicit deep learning neural network model for the prediction of landslide susceptibility

    Dong Van Dao;Abolfazl Jaafari;Mahmoud Bayat;Davood Mafi-Gholami

  • Neural network and particle swarm optimization for predicting the unconfined compressive strength of cemented paste backfill

    Chongchong Qi;Andy Fourie;Qiusong Chen

  • A strength prediction model using artificial intelligence for recycling waste tailings as cemented paste backfill

    Chongchong Qi;Andy Fourie;Qiusong Chen;Qinli Zhang

  • Experimental investigation on the relationship between pore characteristics and unconfined compressive strength of cemented paste backfill

    Lang Liu;Lang Liu;Zhiyu Fang;Chongchong Qi;Bo Zhang

  • Big data management in the mining industry

    Chong chong Qi;Chong chong Qi

  • A new procedure for recycling waste tailings as cemented paste backfill to underground stopes and open pits

    Hongjian Lu;Chongchong Qi;Qiusong Chen;Deqing Gan

  • An experimental study on the early-age hydration kinetics of cemented paste backfill

    Lang Liu;Lang Liu;Pan Yang;Chongchong Qi;Bo Zhang

  • Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping

    Binh Thai Pham;Trung Nguyen-Thoi;Chongchong Qi;Tran Van Phong

  • Experimental investigation on the strength characteristics of cement paste backfill in a similar stope model and its mechanism

    Qiu-song Chen;Qiu-song Chen;Qin-li Zhang;Andy Fourie;Xin Chen

  • An intelligent modelling framework for mechanical properties of cemented paste backfill

    Chongchong Qi;Qiusong Chen;Andy Fourie;Qinli Zhang

  • Co-disposal of magnesium slag and high-calcium fly ash as cementitious materials in backfill

    Lang Liu;Lang Liu;Shishan Ruan;Chongchong Qi;Chongchong Qi;Bo Zhang

  • Permeability prediction of porous media using a combination of computational fluid dynamics and hybrid machine learning methods

    Jianwei Tian;Chongchong Qi;Yingfeng Sun;Zaher Mundher Yaseen

  • Numerical study on the pipe flow characteristics of the cemented paste backfill slurry considering hydration effects

    Lang Liu;Lang Liu;Zhiyu Fang;Chongchong Qi;Bo Zhang

  • Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq

    Khabat Khosravi;Prasad Daggupati;Mohammad Taghi Alami;Salih Muhammad Awadh

  • A Novel Hybrid Soft Computing Model Using Random Forest and Particle Swarm Optimization for Estimation of Undrained Shear Strength of Soil

    Binh Thai Pham;Chongchong Qi;Lanh Si Ho;Trung Nguyen-Thoi

  • Towards Intelligent Mining for Backfill: A genetic programming-based method for strength forecasting of cemented paste backfill

    Chongchong Qi;Xiaolin Tang;Xiangjian Dong;Qiusong Chen

  • Prediction of evaporation in arid and semi-arid regions : a comparative study using different machine learning models

    Zaher Mundher Yaseen;Anas Mahmood Al-Juboori;Ufuk Beyaztas;Nadhir Al-Ansari

  • Immobilization and leaching characteristics of fluoride from phosphogypsum-based cemented paste backfill

    Qiu-song Chen;Shi-yuan Sun;Yi-kai Liu;Yi-kai Liu;Chong-chong Qi

  • Pressure drop in pipe flow of cemented paste backfill: Experimental and modeling study

    Chongchong Qi;Qiusong Chen;Qiusong Chen;Andy Fourie;Jianwen Zhao

  • Mechanics and safety issues in tailing-based backfill: A review

    Xu Zhao;Andy Fourie;Chong chong Qi

Frequent Co-Authors

Andy Fourie
Andy Fourie University of Western Australia
Zaher Mundher Yaseen
Zaher Mundher Yaseen King Fahd University of Petroleum and Minerals
Mohamed Elchalakani
Mohamed Elchalakani University of Western Australia
Indra Prakash
Indra Prakash Geological Survey of India
Nadhir Al-Ansari
Nadhir Al-Ansari Luleå University of Technology
Vijay P. Singh
Vijay P. Singh Texas A&M University
Dieu Tien Bui
Dieu Tien Bui University of South-Eastern Norway
Shamsuddin Shahid
Shamsuddin Shahid University of Technology Malaysia
Sinan Q. Salih
Sinan Q. Salih IEEE Computer Society
Guowei Ma
Guowei Ma University of Western Australia

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