World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
6315
World Ranking
10213
National Ranking
310

Abdul Sattar 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 Abdul Sattar 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: 381 publications — 85th percentile

85% of scientists in this discipline score the same or lower.

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

Abdul Sattar 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 Abdul Sattar 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: 38 D-Index — 30th percentile

30% 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

  • 2015 - ACM Senior Member

Overview

Abdul Sattar is a researcher affiliated with Griffith University in Australia, producing work primarily situated within the fields of Biochemistry, Genetics and Molecular Biology, and Computer Science. Their multidisciplinary focus combines extensive expertise in molecular biology with computational approaches, reflecting a strong emphasis on both life sciences and information technology.

Their research spans several subfields, including Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, and Industrial and Manufacturing Engineering. Sattar's scholarly output covers a wide range of topics, particularly concentrating on Protein Structure and Dynamics, Machine Learning in Bioinformatics, and Computational Drug Discovery Methods. Additional topics in their work include Water Quality Monitoring Technologies, RNA and protein synthesis mechanisms, Enzyme Structure and Function, and Bioinformatics and Genomic Networks.

Their recent notable papers demonstrate this interdisciplinary breadth:

  • "Neurological Manifestations of COVID-19 (SARS-CoV-2): A Review" (2020), published in Frontiers in Neurology
  • "Synthesis, in vitro bio-evaluation, and molecular docking study of thiosemicarbazone-based isatin/bis-Schiff base hybrid analogues as effective cholinesterase inhibitors" (2023), published in Journal of Molecular Structure
  • "Consumer's intention to purchase 5G: Do environmental awareness, environmental knowledge and health consciousness attitude matter?" (2021), published in Technology in Society
  • "Review of modelling and simulation strategies for evaluating corrosive behavior of aqueous amine systems for CO2 capture" (2020), published in International Journal of Greenhouse Gas Control
  • "CardioTox net: a robust predictor for hERG channel blockade based on deep learning meta-feature ensembles" (2021), published in Journal of Cheminformatics

Frequently publishing in venues such as Scientific Reports, SSRN Electronic Journal, and South Asian Journal of Emergency Medicine, Sattar has contributed to journals relating to both scientific research and technological applications. Other common venues include Internet of Things and IEEE Access.

Their collaborative network includes frequent co-authors such as M. A. Hakim Newton, Jarrod Trevathan, Julia Rahman, Abdul Karim, and Abdollah Dehzangi, indicating sustained partnerships across multiple research projects.

In recognition of professional standing, Abdul Sattar was awarded the ACM Senior Member distinction in 2015, reflecting a formal acknowledgment within the computing community.

Best Publications

  • Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning.

    Rhys Heffernan;Kuldip Paliwal;James Lyons;Abdollah Dehzangi

  • Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC

    Abdollah Dehzangi;Abdollah Dehzangi;Rhys Heffernan;Alok Sharma;Alok Sharma;James Lyons

  • Local search with edge weighting and configuration checking heuristics for minimum vertex cover

    Shaowei Cai;Kaile Su;Abdul Sattar

  • SPIDER2: A Package to Predict Secondary Structure, Accessible Surface Area, and Main-Chain Torsional Angles by Deep Neural Networks

    Yuedong Yang;Rhys Heffernan;Kuldip Paliwal;James Lyons

  • Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.

    James G. Lyons;Abdollah Dehzangi;Abdollah Dehzangi;Rhys Heffernan;Alok Sharma;Alok Sharma

  • NuMVC: an efficient local search algorithm for minimum vertex cover

    Shaowei Cai;Kaile Su;Chuan Luo;Abdul Sattar

  • AI 2006: Advances in Artificial Intelligence

    Abdul Sattar;Byeong-Ho Kang

  • EASE-MM: Sequence-Based Prediction of Mutation-Induced Stability Changes with Feature-Based Multiple Models

    Lukas Folkman;Lukas Folkman;Bela Stantic;Abdul Sattar;Abdul Sattar;Yaoqi Zhou

  • INDu : An Interval & Duration Network

    Arun K. Pujari;Arun K. Pujari;G. Vijaya Kumari;G. Vijaya Kumari;Abdul Sattar;Abdul Sattar

  • Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins

    Rhys Heffernan;Abdollah Dehzangi;Abdollah Dehzangi;James G. Lyons;Kuldip K. Paliwal

  • INDU: An Interval and Duration Network

    Arun K. Pujari;G. Vijaya Kumari;Abdul Sattar

  • Twin Removal in Genetic Algorithms for Protein Structure Prediction Using Low-Resolution Model

    Tamjidul Hoque;Madhu Chetty;Andrew Lewis;Abdul Sattar

  • PSSM-Suc: Accurately predicting succinylation using position specific scoring matrix into bigram for feature extraction

    Abdollah Dehzangi;Yosvany López;Sunil Pranit Lal;Ghazaleh Taherzadeh

  • PRICAI 2002: Trends in Artificial Intelligence

    Mitsuru Ishizuka;Abdul Sattar

  • Proposing a highly accurate protein structural class predictor using segmentation-based features.

    Abdollah Dehzangi;Abdollah Dehzangi;Kuldip K. Paliwal;James G. Lyons;Alok Sharma;Alok Sharma

  • A Combination of Feature Extraction Methods with an Ensemble of Different Classifiers for Protein Structural Class Prediction Problem

    Abdollah Dehzangi;Kuldip Paliwal;Alok Sharma;Omid Dehzangi

  • Extended HP model for protein structure prediction.

    Tamjidul Hoque;Madhusudan Rajgopal Chetty;Abdul Sattar

  • Protein folding prediction in 3D FCC HP lattice model using genetic algorithm

    M.T. Hoque;M. Chetty;A. Sattar

  • A defeasible logic for modelling policy-based intentions and motivational attitudes

    Guido Governatori;Vineet Padmanabhan;Antonino Rotolo;Abdul Sattar

  • Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary information from profile bigrams.

    Abdollah Dehzangi;Yosvany López;Sunil Pranit Lal;Ghazaleh Taherzadeh

  • Efficient Toxicity Prediction via Simple Features Using Shallow Neural Networks and Decision Trees

    Abdul Karim;Avinash Mishra;M. A. Hakim Newton;Abdul Sattar

  • A Defeasible Logic of Policy-Based Intention

    Guido Governatori;Vineet Padmanabhan;Abdul Sattar

Frequent Co-Authors

Abdollah Dehzangi
Abdollah Dehzangi Rutgers, The State University of New Jersey
Alok Sharma
Alok Sharma Griffith University
Guido Governatori
Guido Governatori Central Queensland University
Kuldip K. Paliwal
Kuldip K. Paliwal Griffith University
Mehmet A. Orgun
Mehmet A. Orgun Macquarie University
Conrad Sanderson
Conrad Sanderson Commonwealth Scientific and Industrial Research Organisation
Yaoqi Zhou
Yaoqi Zhou Griffith University
Randy Goebel
Randy Goebel University of Alberta
Michael J. Maher
Michael J. Maher University of New South Wales
Tatsuhiko Tsunoda
Tatsuhiko Tsunoda University of Tokyo

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