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D-Index
39
Citations
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694
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42

Computer Science

D-Index
41
Citations
8703
World Ranking
8717
National Ranking
266

Moloud Abdar 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 Moloud Abdar 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: 91 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Moloud Abdar 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 Moloud Abdar 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Moloud Abdar is affiliated with Deakin University in Australia and focuses on research within the field of Computer Science, particularly in Artificial Intelligence. Their publication record includes 82 works in Computer Science, with 60 specifically covering Artificial Intelligence. Subfields of their expertise include Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, and Sociology and Political Science.

The main research topics associated with Moloud Abdar comprise:

  • Anomaly Detection Techniques and Applications
  • AI in cancer detection
  • COVID-19 diagnosis using AI
  • Machine Learning and Data Classification
  • EEG and Brain-Computer Interfaces
  • Metaheuristic Optimization Algorithms Research
  • Adversarial Robustness in Machine Learning

Moloud Abdar has published notable papers which include:

  • A review of uncertainty quantification in deep learning: Techniques, applications and challenges (2021) in Information Fusion
  • Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning (2021) in Computers in Biology and Medicine

Frequent co-authors collaborating with Moloud Abdar are:

  • Abbas Khosravi
  • Saeid Nahavandi
  • U. Rajendra Acharya
  • Vladimir Makarenkov
  • Paweł Pławiak

The venues where Moloud Abdar has frequently published include:

  • arXiv (Cornell University)
  • Information Fusion
  • Knowledge-Based Systems
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Computers in Biology and Medicine

In addition to journal publications, Moloud Abdar has contributed to book literature, including a title published by Springer Nature:

  • Application of Machine Learning and Deep Learning Methods to Power System Problems (2021)

Best Publications

  • A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

    Moloud Abdar;Farhad Pourpanah;Sadiq Hussain;Dana Rezazadegan

  • A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

    Moloud Abdar;Farhad Pourpanah;Sadiq Hussain;Dana Rezazadegan

  • ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis

    Mohammad Ehsan Basiri;Shahla Nemati;Moloud Abdar;Erik Cambria

  • A Review of Generalized Zero-Shot Learning Methods

    Unknown

  • A new machine learning technique for an accurate diagnosis of coronary artery disease

    Moloud Abdar;Wojciech Książek;U Rajendra Acharya;U Rajendra Acharya;U Rajendra Acharya;Ru-San Tan

  • Machine learning-based coronary artery disease diagnosis: A comprehensive review.

    Roohallah Alizadehsani;Moloud Abdar;Mohamad Roshanzamir;Abbas Khosravi

  • Automated Detection of Autism Spectrum Disorder Using a Convolutional Neural Network.

    Zeinab Sherkatghanad;Mohammadsadegh Akhondzadeh;Soorena Salari;Mariam Zomorodi-Moghadam

  • A new nested ensemble technique for automated diagnosis of breast cancer

    Moloud Abdar;Mariam Zomorodi-Moghadam;Xujuan Zhou;Raj Gururajan

  • Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning

    Moloud Abdar;Maryam Samami;Sajjad Dehghani Mahmoodabad;Thang Doan

  • Performance analysis of classification algorithms on early detection of liver disease

    Moloud Abdar;Mariam Zomorodi-Moghadam;Resul Das;I-Hsien Ting

  • A novel fusion-based deep learning model for sentiment analysis of COVID-19 tweets

    Mohammad Ehsan Basiri;Shahla Nemati;Moloud Abdar;Somayeh Asadi

  • Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring

    Paweł Pławiak;Moloud Abdar;U. Rajendra Acharya

  • Comparing Performance of Data Mining Algorithms in Prediction Heart Diseases

    Moloud Abdar;Sharareh R. Niakan Kalhori;Tole Sutikno;Imam Much Ibnu Subroto

  • SpinalNet: Deep Neural Network with Gradual Input.

    H M Dipu Kabir;Moloud Abdar;Seyed Mohammad Jafar Jalali;Abbas Khosravi

  • DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring

    Paweł Pławiak;Moloud Abdar;Joanna Pławiak;Vladimir Makarenkov

  • A novel method for sentiment classification of drug reviews using fusion of deep and machine learning techniques

    Mohammad Ehsan Basiri;Moloud Abdar;Mehmet Aakif Cifci;Shahla Nemati

  • Improving the Diagnosis of Liver Disease Using Multilayer Perceptron Neural Network and Boosted Decision Trees

    Moloud Abdar;Neil Yuwen Yen;Jason Chi-Shun Hung

  • A novel machine learning approach for early detection of hepatocellular carcinoma patients

    Wojciech Książek;Moloud Abdar;U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya;Paweł Pławiak

  • SFE: A Simple, Fast, and Efficient Feature Selection Algorithm for High-Dimensional Data

    Unknown

  • FSS-2019-nCov: A deep learning architecture for semi-supervised few-shot segmentation of COVID-19 infection

    Mohamed Abdel-Basset;Victor Chang;Hossam Hawash;Ripon Kumar Chakrabortty

  • CWV-BANN-SVM ensemble learning classifier for an accurate diagnosis of breast cancer

    Moloud Abdar;Vladimir Makarenkov

  • Association between work-related features and coronary artery disease: A heterogeneous hybrid feature selection integrated with balancing approach

    Elham Nasarian;Moloud Abdar;Mohammad Amin Fahami;Roohallah Alizadehsani

  • Using PSO Algorithm for Producing Best Rules in Diagnosis of Heart Disease

    Azhar Hussein Alkeshuosh;Mariam Zomorodi Moghadam;Inas Al Mansoori;Moloud Abdar

  • A Review of Generalized Zero-Shot Learning Methods.

    Farhad Pourpanah;Moloud Abdar;Yuxuan Luo;Xinlei Zhou

Frequent Co-Authors

U. Rajendra Acharya
U. Rajendra Acharya University of Southern Queensland
Saeid Nahavandi
Saeid Nahavandi Swinburne University of Technology
Abbas Khosravi
Abbas Khosravi Deakin University
Vladimir Makarenkov
Vladimir Makarenkov University of Quebec at Montreal
Roohallah Alizadehsani
Roohallah Alizadehsani Deakin University
Nizal Sarrafzadegan
Nizal Sarrafzadegan Isfahan University of Medical Sciences
Dipti Srinivasan
Dipti Srinivasan National University of Singapore
Ahmed A. Abd El-Latif
Ahmed A. Abd El-Latif Menoufia University
Amir F. Atiya
Amir F. Atiya Cairo University
Mohammad Ghavamzadeh
Mohammad Ghavamzadeh Amazon (United States)

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