World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
14893
World Ranking
9034
National Ranking
3840

Robi Polikar 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 Robi Polikar 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: 190 publications — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Robi Polikar 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 Robi Polikar 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Robi Polikar is affiliated with Rowan University in the United States and has a research focus spanning computer science and biochemistry, genetics, and molecular biology. Their work integrates advanced computational methods with biological and cognitive applications.

The main fields of study for Robi Polikar include:

  • Computer Science
  • Biochemistry, Genetics and Molecular Biology

Subfields of study covered in their publications encompass:

  • Artificial Intelligence
  • Molecular Biology
  • Ecology
  • Psychiatry and Mental health
  • Physiology

Robi Polikar's research topics include:

  • Genomics and Phylogenetic Studies
  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications
  • Domain Adaptation and Few-Shot Learning
  • Machine Learning in Bioinformatics
  • Microbial Community Ecology and Physiology
  • Machine Learning and Data Classification

The scientist has contributed to multiple publication venues, with some of the most frequent being:

  • arXiv (Cornell University)
  • 2021 IEEE Symposium Series on Computational Intelligence (SSCI)
  • PeerJ
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of the International Neuropsychological Society

Among recent papers authored or co-authored by Robi Polikar are:

  • "Machine Learning Analysis of Digital Clock Drawing Test Performance for Differential Classification of Mild Cognitive Impairment Subtypes Versus Alzheimer's Disease," 2020, Journal of the International Neuropsychological Society
  • "Incremental and Semi-Supervised Learning of 16S-rRNA Genes For Taxonomic Classification," 2021, 2021 IEEE Symposium Series on Computational Intelligence (SSCI)
  • "The Naïve Bayes classifier++ for metagenomic taxonomic classification-query evaluation," 2024, Bioinformatics
  • "Incremental & Semi-Supervised Learning for Functional Analysis of Protein Sequences," 2021, 2021 IEEE Symposium Series on Computational Intelligence (SSCI)
  • "Complet+: a computationally scalable method to improve completeness of large-scale protein sequence clustering," 2023, PeerJ

Frequent collaborators with Robi Polikar include:

  • Gail Rosen
  • Bahrad A. Sokhansanj
  • Muhammad Jawad Umer
  • Emrecan Ozdogan
  • G. W. Dawson

Best Publications

  • Ensemble based systems in decision making

    R. Polikar

  • IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS

    Derong Liu;Murad Abu-Khalaf;Adel M. Alimi;Charles Anderson

  • Learn++: an incremental learning algorithm for supervised neural networks

    R. Polikar;L. Upda;S.S. Upda;V. Honavar

  • Multiple Classifier Systems

    Nikunj C. Oza;Robi. Polikar;Josef. Kittler;Fabio. Roli

  • Incremental Learning of Concept Drift in Nonstationary Environments

    R. Elwell;R. Polikar

  • Learning in Nonstationary Environments: A Survey

    Gregory Ditzler;Manuel Roveri;Cesare Alippi;Robi Polikar

  • Incremental Learning of Concept Drift from Streaming Imbalanced Data

    Gregory Ditzler;Robi Polikar

  • Learning from streaming data with concept drift and imbalance: an overview

    T. Ryan Hoens;Robi Polikar;Nitesh V. Chawla

  • Learn $^{++}$ .NC: Combining Ensemble of Classifiers With Dynamically Weighted Consult-and-Vote for Efficient Incremental Learning of New Classes

    M.D. Muhlbaier;A. Topalis;R. Polikar

  • COMPOSE: A Semisupervised Learning Framework for Initially Labeled Nonstationary Streaming Data

    Karl B. Dyer;Robert Capo;Robi Polikar

  • Bootstrap - Inspired Techniques in Computation Intelligence

    R. Polikar

  • The story of wavelets

    Robi Polikar

  • An Ensemble-Based Incremental Learning Approach to Data Fusion

    D. Parikh;R. Polikar

  • Hellinger distance based drift detection for nonstationary environments

    Gregory Ditzler;Robi Polikar

  • Metagenome Fragment Classification Using N-Mer Frequency Profiles

    Gail L. Rosen;Elaine Garbarine;Diamantino Caseiro;Robi Polikar

  • Frequency invariant classification of ultrasonic weld inspection signals

    R. Polikar;L. Udpa;S.S. Udpa;T. Taylor

  • Multi-Layer and Recursive Neural Networks for Metagenomic Classification

    Gregory Ditzler;Robi Polikar;Gail Rosen

  • An ensemble based data fusion approach for early diagnosis of Alzheimer's disease

    Robi Polikar;Apostolos Topalis;Devi Parikh;Deborah Green

  • An architecture for intelligent systems based on smart sensors

    J. Schmalzel;F. Figueroa;J. Morris;S. Mandayam

  • Comparative multiresolution wavelet analysis of ERP spectral bands using an ensemble of classifiers approach for early diagnosis of Alzheimer's disease

    Robi Polikar;Apostolos Topalis;Deborah Green;John Kounios

  • Learn++.MF: A random subspace approach for the missing feature problem

    Robi Polikar;Joseph DePasquale;Hussein Syed Mohammed;Gavin Brown

Frequent Co-Authors

Christopher M. Clark
Christopher M. Clark University of Pennsylvania
John Kounios
John Kounios Drexel University
Satish S. Udpa
Satish S. Udpa Michigan State University
Devi Parikh
Devi Parikh Facebook (United States)
Sharon X. Xie
Sharon X. Xie University of Pennsylvania
Steven E. Arnold
Steven E. Arnold Harvard University
Vasant Honavar
Vasant Honavar Pennsylvania State University
John Q. Trojanowski
John Q. Trojanowski University of Pennsylvania
Virginia M.-Y. Lee
Virginia M.-Y. Lee University of Pennsylvania
Li-San Wang
Li-San Wang University of Pennsylvania

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