World's Best Scientists 2026 revealed!
Nizar Bouguila

Nizar Bouguila

D-Index & Metrics

Computer Science

D-Index
55
Citations
10474
World Ranking
4367
National Ranking
173

Nizar Bouguila 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 Nizar Bouguila 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: 554 publications — 95th percentile

95% of scientists in this discipline score the same or lower.

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

Nizar Bouguila 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 Nizar Bouguila 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Overview

Nizar Bouguila is affiliated with Concordia University in Canada, focusing primarily on research intersecting computer science and engineering disciplines. Their work spans a substantial number of publications within the domain of artificial intelligence, computer vision and pattern recognition, and electrical and electronic engineering.

Their research efforts are significantly represented in several main fields of study: computer science, with a major emphasis on artificial intelligence, as well as engineering. Within these broad fields, Bouguila's contributions cover subfields such as artificial intelligence, computer vision and pattern recognition, electrical and electronic engineering, signal processing, and statistics and probability.

The topics central to their research include Bayesian methods and mixture models, advanced clustering algorithms, text and document classification technologies, topic modeling, image retrieval and classification techniques, face and expression recognition, and anomaly detection techniques and applications.

Nizar Bouguila has published in multiple recognized venues frequently, with seven publications each in IEEE Transactions on Neural Networks and Learning Systems, Sensors, Pattern Analysis and Applications, Applied Intelligence, and the Proceedings of the International Florida Artificial Intelligence Research Society Conference.

Recent notable papers authored by or with involvement of Bouguila include:

  • "On Short-Term Load Forecasting Using Machine Learning Techniques and a Novel Parallel Deep LSTM-CNN Approach" (2021, IEEE Access)
  • "Graph Neural Networks for Intelligent Transportation Systems: A Survey" (2023, IEEE Transactions on Intelligent Transportation Systems)
  • "BLOCK-DBSCAN: Fast clustering for large scale data" (2020, Pattern Recognition)
  • "Clustering Analysis via Deep Generative Models With Mixture Models" (2020, IEEE Transactions on Neural Networks and Learning Systems)
  • "A new workflow for detailed urban scale building energy modeling using spatial joining of attributes for archetype selection" (2021, Journal of Building Engineering)

Collaborations play a significant role in their scientific output, with frequent coauthors including Manar Amayri, Wentao Fan, Narges Manouchehri, Fatma Najar, and Muhammad Azam.

Best Publications

  • On Short-Term Load Forecasting Using Machine Learning Techniques and a Novel Parallel Deep LSTM-CNN Approach

    Behnam Farsi;Manar Amayri;Nizar Bouguila;Ursula Eicker

  • Unsupervised learning of a finite mixture model based on the Dirichlet distribution and its application

    N. Bouguila;D. Ziou;J. Vaillancourt

  • High-Dimensional Unsupervised Selection and Estimation of a Finite Generalized Dirichlet Mixture Model Based on Minimum Message Length

    N. Bouguila;D. Ziou

  • A Fast Clustering Algorithm based on pruning unnecessary distance computations in DBSCAN for High-Dimensional Data

    Yewang Chen;Yewang Chen;Shengyu Tang;Nizar Bouguila;Cheng Wang

  • A Hybrid Feature Extraction Selection Approach for High-Dimensional Non-Gaussian Data Clustering

    S. Boutemedjet;N. Bouguila;D. Ziou

  • Unsupervised selection of a finite Dirichlet mixture model: an MML-based approach

    N. Bouguila;D. Ziou

  • BLOCK-DBSCAN: Fast clustering for large scale data

    Yewang Chen;Lida Zhou;Nizar Bouguila;Cheng Wang

  • Variational Learning for Finite Dirichlet Mixture Models and Applications

    Wentao Fan;N. Bouguila;D. Ziou

  • Practical Bayesian estimation of a finite beta mixture through gibbs sampling and its applications

    Nizar Bouguila;Djemel Ziou;Ernest Monga

  • Finite general Gaussian mixture modeling and application to image and video foreground segmentation

    Mohand Saïd Allili;Nizar Bouguila;Djemel Ziou

  • A study of spam filtering using support vector machines

    Ola Amayri;Nizar Bouguila

  • Network Anomaly Intrusion Detection Using a Nonparametric Bayesian Approach and Feature Selection

    Wajdi Alhakami;Abdullah ALharbi;Sami Bourouis;Roobaea Alroobaea

  • Clustering of Count Data Using Generalized Dirichlet Multinomial Distributions

    N. Bouguila

  • A hybrid SEM algorithm for high-dimensional unsupervised learning using a finite generalized Dirichlet mixture

    N. Bouguila;D. Ziou

  • Count Data Modeling and Classification Using Finite Mixtures of Distributions

    Nizar Bouguila

  • Positive vectors clustering using inverted Dirichlet finite mixture models

    Taoufik Bdiri;Nizar Bouguila

  • Hybrid Generative/Discriminative Approaches for Proportional Data Modeling and Classification

    N. Bouguila

  • A Dirichlet Process Mixture of Generalized Dirichlet Distributions for Proportional Data Modeling

    N. Bouguila;D. Ziou

  • Bayesian learning of finite generalized Gaussian mixture models on images

    Tarek Elguebaly;Nizar Bouguila

  • A Robust Video Foreground Segmentation by Using Generalized Gaussian Mixture Modeling

    M.S. Allili;N. Bouguila;D. Ziou

  • Fast neighbor search by using revised k-d tree

    Yewang Chen;Lida Zhou;Yi Tang;Jai Puneet Singh

Frequent Co-Authors

Djemel Ziou
Djemel Ziou Université de Sherbrooke
Ji-Xiang Du
Ji-Xiang Du Huaqiao University
Jamal Bentahar
Jamal Bentahar Concordia University
A. Ben Hamza
A. Ben Hamza Concordia University
Douglas L. Arnold
Douglas L. Arnold Montreal Neurological Institute and Hospital
Safya Belghith
Safya Belghith National Engineering School of Tunis
Bineng Zhong
Bineng Zhong Guangxi Normal University
Ali Ghrayeb
Ali Ghrayeb Hamad bin Khalifa University
Reinaldo A. Valenzuela
Reinaldo A. Valenzuela Nokia (United States)
Chadi Assi
Chadi Assi Concordia University

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