World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
7757
World Ranking
9643
National Ranking
4085

Nagiza F. Samatova 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 Nagiza F. Samatova 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: 192 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.

Nagiza F. Samatova 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 Nagiza F. Samatova 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Nagiza F. Samatova is affiliated with North Carolina State University in the United States. Their research spans the fields of Mathematics and Computer Science, with a focus on subfields such as Artificial Intelligence, Statistical and Nonlinear Physics, Applied Mathematics, Oceanography, and Mathematical Physics.

The primary topics addressed in their work include Nonlinear Waves and Solitons, Navier-Stokes equation solutions, Ocean Waves and Remote Sensing, Advanced Mathematical Physics Problems, Machine Learning and Data Classification, Imbalanced Data Classification Techniques, and Data Stream Mining Techniques.

Their recent publications include:

  • "Group classification of the two-dimensional shallow water equations with the beta-plane approximation of coriolis parameter in Lagrangian coordinates", 2020, Communications in Nonlinear Science and Numerical Simulation
  • "The one-dimensional Green-Naghdi equations with a time dependent bottom topography and their conservation laws", 2020, Physics of Fluids
  • "Predictive models with end user preference", 2021, Statistical Analysis and Data Mining The ASA Data Science Journal
  • "An analysis of junior rower performance and how it is affected by rower's features", 2022, Journal of Emerging Investigators

Frequent collaborators in their research include Sergey V. Meleshko, Е. И. Капцов, Yifan Zhao, Yang Xian, and Carolina Bolnykh.

The venues in which their work has appeared reflect their interdisciplinary interests and include Communications in Nonlinear Science and Numerical Simulation, Physics of Fluids, Statistical Analysis and Data Mining The ASA Data Science Journal, and Journal of Emerging Investigators.

Best Publications

  • Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

    Anuj Karpatne;Gowtham Atluri;James H. Faghmous;Michael Steinbach

  • Detecting Differential and Correlated Protein Expression in Label-Free Shotgun Proteomics

    Bing Zhang;Nathan C. Verberkmoes;Michael A. Langston;Edward Uberbacher

  • Anomaly detection in dynamic networks: a survey

    Stephen Ranshous;Stephen Ranshous;Shitian Shen;Shitian Shen;Danai Koutra;Steve Harenberg;Steve Harenberg

  • Gene network shaping of inherent noise spectra

    D. Austin;D. Austin;M. Allen;J. Mccollum;R. Dar

  • Community detection in large‐scale networks: a survey and empirical evaluation

    Steve Harenberg;Steve Harenberg;Gonzalo Bello;Gonzalo Bello;L. Gjeltema;L. Gjeltema;Stephen Ranshous;Stephen Ranshous

  • Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks

    Qing Liu;Jeremy Logan;Yuan Tian;Hasan Abbasi

  • The sorting direct method for stochastic simulation of biochemical systems with varying reaction execution behavior

    James M. McCollum;Gregory D. Peterson;Chris D. Cox;Michael L. Simpson

  • Compressing the incompressible with ISABELA: in-situ reduction of spatio-temporal data

    Sriram Lakshminarasimhan;Neil Shah;Stephane Ethier;Scott Klasky

  • A scalable, parallel algorithm for maximal clique enumeration

    Matthew C. Schmidt;Nagiza F. Samatova;Kevin Thomas;Byung-Hoon Park

  • From pull-down data to protein interaction networks and complexes with biological relevance

    Bing Zhang;Byung-Hoon Park;Tatiana Karpinets;Nagiza F. Samatova

  • Community-based anomaly detection in evolutionary networks

    Zhengzhang Chen;William Hendrix;Nagiza F. Samatova

  • Method for gathering and summarizing internet information

    Thomas E. Potok;Mark Thomas Elmore;Joel Wesley Reed;Jim N. Treadwell

  • Improved genome annotation for Zymomonas mobilis.

    Shihui Yang;Katherine M Pappas;Loren J Hauser;Miriam L Land

  • ProRata: A quantitative proteomics program for accurate protein abundance ratio estimation with confidence interval evaluation.

    Chongle Pan;Guruprasad H Kora;W Hayes McDonald;Dave L Tabb

  • ISABELA for effective in situ compression of scientific data

    Sriram Lakshminarasimhan;Sriram Lakshminarasimhan;Neil Shah;Stéphane Ethier;Seung-Hoe Ku

  • Efficient data access for parallel BLAST

    Heshan Lin;Xiaosong Ma;P. Chandramohan;A. Geist

  • Genome-Scale Computational Approaches to Memory-Intensive Applications in Systems Biology

    Yun Zhang;Faisal N. Abu-Khzam;Nicole E. Baldwin;Elissa J. Chesler

  • Learning Entity Type Embeddings for Knowledge Graph Completion

    Changsung Moon;Paul Jones;Nagiza F. Samatova

  • ISABELA-QA: query-driven analytics with ISABELA-compressed extreme-scale scientific data

    Sriram Lakshminarasimhan;John Jenkins;Isha Arkatkar;Zhenhuan Gong

  • RACHET: An Efficient Cover-Based Merging of Clustering Hierarchies from Distributed Datasets

    Nagiza F. Samatova;George Ostrouchov;Al Geist;Anatoli V. Melechko

  • An Introduction to Graph Theory

    Nagiza F. Samatova;William Hendrix;John Jenkins;Kanchana Padmanabhan

  • Theory-guided Data Science: A New Paradigm for Scientific Discovery.

    Anuj Karpatne;Gowtham Atluri;James H. Faghmous;Michael S. Steinbach

  • Scientific Data Analysis.

    Chandrika Kamath;Nikil Wale;George Karypis;Gaurav Pandey

Frequent Co-Authors

Scott Klasky
Scott Klasky Oak Ridge National Laboratory
Vipin Kumar
Vipin Kumar University of Minnesota
Robert Ross
Robert Ross Argonne National Laboratory
Alok Choudhary
Alok Choudhary Northwestern University
Robert L. Hettich
Robert L. Hettich Oak Ridge National Laboratory
P. Murali Doraiswamy
P. Murali Doraiswamy Duke University
Michael L. Simpson
Michael L. Simpson University of Tennessee at Knoxville
James R. Mihelcic
James R. Mihelcic University of South Florida
Kesheng Wu
Kesheng Wu Lawrence Berkeley National Laboratory
Dale A. Pelletier
Dale A. Pelletier Oak Ridge National Laboratory

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