World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
7908
World Ranking
5967
National Ranking
58

Pijush Samui publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Pijush Samui sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 224 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Pijush Samui D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Pijush Samui sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Pijush Samui is affiliated with the National Institute of Technology Patna in India. Their research primarily spans the fields of engineering and environmental science, with a strong focus on civil and structural engineering, safety, risk, reliability and quality, as well as environmental engineering. Their body of work demonstrates a sustained interest in geotechnical engineering and analysis, dam engineering and safety, along with landslides and related hazards.

The scientist's research themes include:

  • Geotechnical Engineering and Analysis
  • Dam Engineering and Safety
  • Geotechnical Engineering and Underground Structures
  • Landslides and related hazards
  • Geotechnical Engineering and Soil Mechanics
  • Rock Mechanics and Modeling
  • Infrastructure Maintenance and Monitoring

Pijush Samui has published extensively, with notable presence in key journals such as the International Journal of Advanced Intelligence Paradigms, Modeling Earth Systems and Environment, Arabian Journal of Geosciences, Geotechnical and Geological Engineering, and Frontiers of Structural and Civil Engineering.

Frequent publication venues include:

  • International Journal of Advanced Intelligence Paradigms
  • Modeling Earth Systems and Environment
  • Arabian Journal of Geosciences
  • Geotechnical and Geological Engineering
  • Frontiers of Structural and Civil Engineering

Co-authors frequently collaborating with Pijush Samui encompass Abidhan Bardhan, Divesh Ranjan Kumar, Avijit Burman, Danial Jahed Armaghani, and Deepak Kumar.

Frequent co-authors are:

  • Abidhan Bardhan
  • Divesh Ranjan Kumar
  • Avijit Burman
  • Danial Jahed Armaghani
  • Deepak Kumar

Their recent papers include the following:

  • "Effectiveness assessment of Keras based deep learning with different robust optimization algorithms for shallow landslide susceptibility mapping at tropical area" (2020, CATENA)
  • "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)
  • "Application of soft computing techniques for shallow foundation reliability in geotechnical engineering" (2020, Geoscience Frontiers)
  • "Efficient computational techniques for predicting the California bearing ratio of soil in soaked conditions" (2021, Engineering Geology)
  • "Closed-Form Equation for Estimating Unconfined Compressive Strength of Granite from Three Non-destructive Tests Using Soft Computing Models" (2022, Rock Mechanics and Rock Engineering)

Pijush Samui has contributed to academic literature through book publications associated with publishers such as Springer International Publishing and the University of Southern Queensland. Titles include Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation published in 2020 and Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation published in 2021.

Best Publications

  • Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models

    Panagiotis G. Asteris;Athanasia D. Skentou;Abidhan Bardhan;Pijush Samui

  • A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area.

    Dieu Tien Bui;Nhat-Duc Hoang;Francisco Martínez-Álvarez;Phuong-Thao Thi Ngo

  • A novel hybrid approach based on a swarm intelligence optimized extreme learning machine for flash flood susceptibility mapping

    Dieu Tien Bui;Phuong-Thao Thi Ngo;Tien Dat Pham;Abolfazl Jaafari

  • Support vector machine applied to settlement of shallow foundations on cohesionless soils

    Pijush Samui

  • Slope stability analysis: a support vector machine approach

    Pijush Samui

  • Machine learning modelling for predicting soil liquefaction susceptibility

    P. Samui;T. G. Sitharam

  • Assessment of pile drivability using random forest regression and multivariate adaptive regression splines

    Wengang Zhang;Chongzhi Wu;Yongqin Li;Lin Wang

  • Application of Artificial Intelligence to Maximum Dry Density and Unconfined Compressive Strength of Cement Stabilized Soil

    Sarat Kumar Das;Pijush Samui;Akshaya K. Sabat

  • Utilization of a least square support vector machine (LSSVM) for slope stability analysis

    P. Samui;D.P. Kothari

  • A Novel Hybrid Swarm Optimized Multilayer Neural Network for Spatial Prediction of Flash Floods in Tropical Areas Using Sentinel-1 SAR Imagery and Geospatial Data.

    Phuong-Thao Thi Ngo;Nhat-Duc Hoang;Biswajeet Pradhan;Biswajeet Pradhan;Quang Khanh Nguyen

  • Effectiveness assessment of Keras based deep learning with different robust optimization algorithms for shallow landslide susceptibility mapping at tropical area

    Viet-Ha Nhu;Nhat-Duc Hoang;Hieu Nguyen;Phuong Thao Thi Ngo

  • Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models

    Ravinesh C. Deo;Pijush Samui;Dookie Kim

  • Forecasting monthly precipitation using sequential modelling

    Deepak Kumar;Anshuman Singh;Pijush Samui;Rishi Kumar Jha

  • 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

  • Forecasting heating and cooling loads of buildings: a comparative performance analysis

    Sanjiban Sekhar Roy;Pijush Samui;Ishan Nagtode;Hemant Jain

  • Compressive strength prediction of high-performance concrete using gradient tree boosting machine

    Mosbeh R. Kaloop;Mosbeh R. Kaloop;Deepak Kumar;Pijush Samui;Jong Wan Hu

  • Spatial pattern analysis and prediction of forest fire using new machine learning approach of Multivariate Adaptive Regression Splines and Differential Flower Pollination optimization: A case study at Lao Cai province (Viet Nam).

    Dieu Tien Bui;Dieu Tien Bui;Nhat-Duc Hoang;Pijush Samui

  • Application of soft computing techniques for shallow foundation reliability in geotechnical engineering

    Rahul Ray;Deepak Kumar;Pijush Samui;Lal Bahadur Roy

  • Prediction of compressive strength of self-compacting concrete using least square support vector machine and relevance vector machine

    Bhairevi Ganesh Aiyer;Dookie Kim;Nithin Karingattikkal;Pijush Samui

  • Application of support vector machine and relevance vector machine to determine evaporative losses in reservoirs

    Pijush Samui;Barnali M. Dixon

  • Efficient computational techniques for predicting the California bearing ratio of soil in soaked conditions

    Abidhan Bardhan;Candan Gokceoglu;Avijit Burman;Pijush Samui

  • Modelling the energy performance of residential buildings using advanced computational frameworks based on RVM, GMDH, ANFIS-BBO and ANFIS-IPSO

    Navid Kardani;Abidhan Bardhan;Dookie Kim;Pijush Samui

Frequent Co-Authors

T. G. Sitharam
T. G. Sitharam Indian Institute of Technology Guwahati
Dieu Tien Bui
Dieu Tien Bui University of South-Eastern Norway
Nhat-Duc Hoang
Nhat-Duc Hoang Duy Tan University
Ravinesh C. Deo
Ravinesh C. Deo University of Southern Queensland
Hossein Bonakdari
Hossein Bonakdari University of Ottawa
Annan Zhou
Annan Zhou RMIT University
Zaher Mundher Yaseen
Zaher Mundher Yaseen King Fahd University of Petroleum and Minerals
Wengang Zhang
Wengang Zhang Chongqing University
Isa Ebtehaj
Isa Ebtehaj Université Laval
Danial Jahed Armaghani
Danial Jahed Armaghani University of Technology Sydney

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