World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
8345
World Ranking
11469
National Ranking
4711

Naeem Seliya 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 Naeem Seliya 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: 107 publications — 11th percentile

11% of scientists in this discipline score the same or lower.

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

Naeem Seliya 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 Naeem Seliya 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

Naeem Seliya is affiliated with the University of Wisconsin-Eau Claire in the United States. Their research predominantly lies within the domain of computer science, with a primary focus on artificial intelligence, information systems, and signal processing. The scientist has contributed extensively to subfields such as computer networks and communications as well as human-computer interaction.

Their work covers a range of main topics, including user authentication and security systems, advanced malware detection techniques, and IoT and edge/fog computing. Additional areas of interest encompass anomaly detection techniques and applications, context-aware activity recognition systems, biometric identification and security, and network security and intrusion detection.

Frequently collaborating with other researchers, Naeem Seliya's notable coauthors include Rushit Dave, Nyle Siddiqui, Mounika Vanamala, Jacob Mallet, and Taghi M. Khoshgoftaar. These collaborations have been spread across multiple projects and publications.

Seliya's research outputs have appeared in various publication venues, with multiple papers published in the following outlets:

  • arXiv (Cornell University)
  • Journal Of Big Data
  • Journal of Computer Sciences and Applications
  • 2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)
  • 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)

Among their recent papers are:

  • A literature review on one-class classification and its potential applications in big data (2021, Journal Of Big Data)
  • Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection (2021, Information)
  • Machine and Deep Learning Applications to Mouse Dynamics for Continuous User Authentication (2022, Machine Learning and Knowledge Extraction)
  • A Modern Analysis of Aging Machine Learning Based IoT Cybersecurity Methods (2021, Journal of Computer Sciences and Applications)
  • The Benefits of Edge Computing in Healthcare, Smart Cities, and IoT (2021, Journal of Computer Sciences and Applications)

Best Publications

  • Deep learning applications and challenges in big data analytics

    Maryam M Najafabadi;Flavio Villanustre;Taghi M Khoshgoftaar;Naeem Seliya

  • A survey on addressing high-class imbalance in big data

    Joffrey L. Leevy;Taghi M. Khoshgoftaar;Richard A. Bauder;Naeem Seliya

  • Choosing software metrics for defect prediction: an investigation on feature selection techniques

    Kehan Gao;Taghi M. Khoshgoftaar;Huanjing Wang;Naeem Seliya

  • A Study on the Relationships of Classifier Performance Metrics

    Naeem Seliya;Taghi M. Khoshgoftaar;Jason Van Hulse

  • Comparative Assessment of Software Quality Classification Techniques: An Empirical Case Study

    Taghi M. Khoshgoftaar;Naeem Seliya

  • Analyzing software measurement data with clustering techniques

    S. Zhong;T.M. Khoshgoftaar;N. Seliya

  • Tree-based software quality estimation models for fault prediction

    T.M. Khoshgoftaar;N. Seliya

  • Attribute Selection and Imbalanced Data: Problems in Software Defect Prediction

    Taghi M. Khoshgoftaar;Kehan Gao;Naeem Seliya

  • Fault Prediction Modeling for Software Quality Estimation: Comparing Commonly Used Techniques

    Taghi M. Khoshgoftaar;Naeem Seliya

  • Evolutionary Optimization of Software Quality Modeling with Multiple Repositories

    Yi Liu;Taghi M Khoshgoftaar;Naeem Seliya

  • A literature review on one-class classification and its potential applications in big data

    Naeem Seliya;Azadeh Abdollah Zadeh;Taghi M. Khoshgoftaar

  • CLUSTERING-BASED NETWORK INTRUSION DETECTION

    Shi Zhong;Taghi M. Khoshgoftaar;Naeem Seliya

  • Software Quality Classification Modeling Using the SPRINT Decision Tree Algorithm

    Taghi M. Khoshgoftaar;Naeem Seliya

  • Unsupervised learning for expert-based software quality estimation

    Shi Zhong;T.M. Khoshgoftaar;N. Seliya

  • A survey on the state of healthcare upcoding fraud analysis and detection

    Richard Bauder;Taghi M. Khoshgoftaar;Naeem Seliya

  • An empirical study of predicting software faults with case-based reasoning

    Taghi M. Khoshgoftaar;Naeem Seliya;Nandini Sundaresh

  • Analogy-Based Practical Classification Rules for Software Quality Estimation

    Taghi M. Khoshgoftaar;Naeem Seliya

  • Software Quality Analysis of Unlabeled Program Modules With Semisupervised Clustering

    N. Seliya;T.M. Khoshgoftaar

  • Software quality estimation with limited fault data: a semi-supervised learning perspective

    Naeem Seliya;Taghi M. Khoshgoftaar

  • Machine Learning for Detecting Brute Force Attacks at the Network Level

    Maryam M. Najafabadi;Taghi M. Khoshgoftaar;Clifford Kemp;Naeem Seliya

Frequent Co-Authors

Taghi M. Khoshgoftaar
Taghi M. Khoshgoftaar Florida Atlantic University
Bojan Cukic
Bojan Cukic University of North Carolina at Charlotte
Mayuram S. Krishnan
Mayuram S. Krishnan University of Michigan–Ann Arbor
Wei Biao Wu
Wei Biao Wu University of Chicago
Tridas Mukhopadhyay
Tridas Mukhopadhyay Carnegie Mellon University

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