World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
4443
World Ranking
12713
National Ranking
32

Liyana Shuib 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 Liyana Shuib 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: 102 publications — 9th percentile

9% of scientists in this discipline score the same or lower.

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

Liyana Shuib 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 Liyana Shuib 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: 33 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Overview

Liyana Shuib is affiliated with the University of Malaya in Malaysia and has a research profile primarily situated within the fields of Computer Science and Social Sciences. Their work encompasses a range of subfields including Artificial Intelligence, Information Systems, Sociology and Political Science, Information Systems and Management, and Education.

The main research topics covered by Liyana Shuib include:

  • Technology Adoption and User Behaviour
  • Sentiment Analysis and Opinion Mining
  • Mobile Learning in Education
  • Online Learning and Analytics
  • Digital Marketing and Social Media
  • Advanced Text Analysis Techniques
  • Artificial Intelligence in Healthcare and Education

Recent representative papers authored or coauthored by Liyana Shuib are:

  • Big data in education: a state of the art, limitations, and future research directions, 2020, published in International Journal of Educational Technology in Higher Education
  • Drivers and inhibitors for digital payment adoption using the Cashless Society Readiness-Adoption model in Malaysia, 2021, Technology in Society
  • For Sustainable Application of Mobile Learning: An Extended UTAUT Model to Examine the Effect of Technical Factors on the Usage of Mobile Devices as a Learning Tool, 2021, Sustainability
  • Assessment of sustainability indicators for green building manufacturing using fuzzy multi-criteria decision making approach, 2020, Journal of Cleaner Production
  • Context-Based Feature Technique for Sarcasm Identification in Benchmark Datasets Using Deep Learning and BERT Model, 2021, IEEE Access

Frequent collaborative partnerships in research include coauthors:

  • Elaheh Yadegaridehkordi
  • Christopher Ifeanyi Eke
  • Ainuddin Wahid Abdul Wahab
  • Maria Ijaz Baig
  • Amirrudin Kamsin

Liyana Shuib regularly publishes in venues such as:

  • IEEE Access
  • Sustainability
  • Malaysian Journal of Computer Science
  • Neural Computing and Applications
  • Electronic Government an International Journal

Best Publications

  • Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Mohammad Tubishat;Norisma Idris;Liyana Shuib;Mohammad A.M. Abushariah

  • Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges

    Ghulam Murtaza;Ghulam Murtaza;Liyana Shuib;Ainuddin Wahid Abdul Wahab;Ghulam Mujtaba

  • Identification of personal traits in adaptive learning environment: Systematic literature review

    Nur Baiti Afini Normadhi;Liyana Shuib;Hairul Nizam Md Nasir;Andrew Bimba

  • Big data adoption: State of the art and research challenges

    Maria Ijaz Baig;Liyana Shuib;Elaheh Yadegaridehkordi

  • Big data in education: a state of the art, limitations, and future research directions

    Maria Ijaz Baig;Liyana Shuib;Elaheh Yadegaridehkordi

  • Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach

    Elaheh Yadegaridehkordi;Mehdi Hourmand;Mehrbakhsh Nilashi;Mehrbakhsh Nilashi;Liyana Shuib

  • Social Media Recommender Systems: Review and Open Research Issues

    Anitha Anandhan;Liyana Shuib;Maizatul Akmar Ismail;Ghulam Mujtaba

  • A Survey of User Profiling: State-of-the-Art, Challenges, and Solutions

    Christopher Ifeanyi Eke;Azah Anir Norman;Liyana Shuib;Henry Friday Nweke

  • The impact of big data on firm performance in hotel industry

    Elaheh Yadegaridehkordi;Mehrbakhsh Nilashi;Liyana Shuib;Mohd Hairul Nizam Bin Md Nasir

  • Email Classification Research Trends: Review and Open Issues

    Ghulam Mujtaba;Liyana Shuib;Ram Gopal Raj;Nahdia Majeed

  • Assessment of sustainability indicators for green building manufacturing using fuzzy multi-criteria decision making approach

    Elaheh Yadegaridehkordi;Mehdi Hourmand;Mehrbakhsh Nilashi;Eesa Alsolami

  • For Sustainable Application of Mobile Learning: An Extended UTAUT Model to Examine the Effect of Technical Factors on the Usage of Mobile Devices as a Learning Tool

    Saud S. Alghazi;Amirrudin Kamsin;Mohammed Amin Almaiah;Seng Yue Wong

  • Context-Based Feature Technique for Sarcasm Identification in Benchmark Datasets Using Deep Learning and BERT Model

    Christopher Ifeanyi Eke;Azah Anir Norman;Liyana Shuib

  • Mobile Learning for English Language Acquisition: Taxonomy, Challenges, and Recommendations

    Monther M. Elaish;Liyana Shuib;Norjihan Abdul Ghani;Elaheh Yadegaridehkordi

  • Clinical text classification research trends: Systematic literature review and open issues

    Ghulam Mujtaba;Ghulam Mujtaba;Liyana Shuib;Norisma Idris;Wai Lam Hoo

  • Mobile English Language Learning (MELL): a literature review

    Monther M. Elaish;Liyana Shuib;Norjihan Abdul Ghani;Elaheh Yadegaridehkordi

  • Sarcasm identification in textual data: systematic review, research challenges and open directions

    Christopher Ifeanyi Eke;Christopher Ifeanyi Eke;Azah Anir Norman;Liyana Shuib;Henry Friday Nweke;Henry Friday Nweke

  • A review of mobile pervasive learning

    Liyana Shuib;Shahaboddin Shamshirband;Mohammad Hafiz Ismail

  • Decision to adopt online collaborative learning tools in higher education: A case of top Malaysian universities

    Elaheh Yadegaridehkordi;Liyana Shuib;Mehrbakhsh Nilashi;Shahla Asadi

  • Bio-inspired computation: Recent development on the modifications of the cuckoo search algorithm

    Haruna Chiroma;Tutut Herawan;Iztok Fister;Sameem Abdulkareem

Frequent Co-Authors

Tutut Herawan
Tutut Herawan University of Malaya
Ainuddin Wahid Abdul Wahab
Ainuddin Wahid Abdul Wahab Information Technology University
Absalom E. Ezugwu
Absalom E. Ezugwu North-West University
Othman Ibrahim
Othman Ibrahim University of Technology Malaysia
Mohammed Amin Almaiah
Mohammed Amin Almaiah University of Jordan
Gwo-Jen Hwang
Gwo-Jen Hwang National Taiwan University of Science and Technology
David Nicholas
David Nicholas CIBER Research
Shahab S. Band
Shahab S. Band National Yunlin University of Science and Technology
Iztok Fister
Iztok Fister University of Maribor

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