World's Best Scientists 2026 revealed!
Sengul Dogan

Sengul Dogan

Award Badge
Computer Science
Turkey
2026

D-Index & Metrics

Computer Science

D-Index
45
Citations
6534
World Ranking
7310
National Ranking
10

Sengul Dogan 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 Sengul Dogan 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: 240 publications — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Sengul Dogan 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 Sengul Dogan 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: 45 D-Index — 51st percentile

51% 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

  • 2026 - Research.com Computer Science in Turkey Leader Award

Overview

Sengul Dogan is a researcher affiliated with Fırat University in Turkey, contributing extensively to the fields of Computer Science and Medicine. Their work spans a broad range of interdisciplinary topics, integrating advanced computational techniques with medical and cognitive neuroscience applications.

The main fields of study for Sengul Dogan include:

  • Computer Science
  • Medicine

The researcher's subfields cover:

  • Cognitive Neuroscience
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging

Key research topics encompass:

  • EEG and Brain-Computer Interfaces
  • ECG Monitoring and Analysis
  • Music and Audio Processing
  • COVID-19 diagnosis using AI
  • Emotion and Mood Recognition
  • Speech and Audio Processing
  • Phonocardiography and Auscultation Techniques

Several recent publications showcase Sengul Dogan's contribution to both methodological advances and applied biomedical signal analysis:

  • "An automated Residual Exemplar Local Binary Pattern and iterative ReliefF based COVID-19 detection method using chest X-ray image" (2020), published in Chemometrics and Intelligent Laboratory Systems
  • "Surface EMG signal classification using ternary pattern and discrete wavelet transform based feature extraction for hand movement recognition" (2020), published in Biomedical Signal Processing and Control
  • "EEG-based emotion recognition using tunable Q wavelet transform and rotation forest ensemble classifier" (2021), published in Biomedical Signal Processing and Control
  • "Automated accurate speech emotion recognition system using twine shuffle pattern and iterative neighborhood component analysis techniques" (2020), published in Knowledge-Based Systems
  • "Automated ASD detection using hybrid deep lightweight features extracted from EEG signals" (2021), published in Computers in Biology and Medicine

Frequent co-authors in Sengul Dogan's body of work include:

  • Türker Tuncer
  • U. Rajendra Acharya
  • Prabal Datta Barua
  • Mehmet Bayğın

Publishing activity is notably concentrated in the following venues:

  • Multimedia Tools and Applications
  • Biomedical Signal Processing and Control
  • Diagnostics
  • Expert Systems with Applications
  • Cognitive Neurodynamics

This profile illustrates Sengul Dogan's multidisciplinary approach at the intersection of computing and biomedical sciences, with particular emphasis on signal processing and artificial intelligence applications in healthcare diagnostics and cognitive neuroscience.

Best Publications

  • Automated arrhythmia detection using novel hexadecimal local pattern and multilevel wavelet transform with ECG signals

    Turker Tuncer;Sengul Dogan;Paweł Pławiak;U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya

  • An automated Residual Exemplar Local Binary Pattern and iterative ReliefF based COVID-19 detection method using chest X-ray image.

    Turker Tuncer;Sengul Dogan;Fatih Ozyurt

  • Surface EMG signal classification using ternary pattern and discrete wavelet transform based feature extraction for hand movement recognition

    Turker Tuncer;Sengul Dogan;Abdulhamit Subasi

  • EEG-based emotion recognition using tunable Q wavelet transform and rotation forest ensemble classifier

    Abdulhamit Subasi;Abdulhamit Subasi;Turker Tuncer;Sengul Dogan;Dahiru Tanko

  • Automated accurate speech emotion recognition system using twine shuffle pattern and iterative neighborhood component analysis techniques

    Turker Tuncer;Sengul Dogan;U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya

  • Automated ASD detection using hybrid deep lightweight features extracted from EEG signals.

    Mehmet Baygin;Sengul Dogan;Turker Tuncer;Prabal Datta Barua

  • GaborPDNet: Gabor Transformation and Deep Neural Network for Parkinson’s Disease Detection Using EEG Signals

    Hui Wen Loh;Chui Ping Ooi;Elizabeth Palmer;Prabal Datta Barua

  • Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice

    Turker Tuncer;Sengul Dogan;Fatih Özyurt;Samir Brahim Belhaouari

  • Automated detection of Parkinson's disease using minimum average maximum tree and singular value decomposition method with vowels

    Turker Tuncer;Sengul Dogan;Udyavara Rajendra Acharya;Udyavara Rajendra Acharya;Udyavara Rajendra Acharya

  • Automated accurate fire detection system using ensemble pretrained residual network

    Unknown

  • Epilepsy detection in 121 patient populations using hypercube pattern from EEG signals

    Unknown

  • A new fractal pattern feature generation function based emotion recognition method using EEG

    Turker Tuncer;Sengul Dogan;Abdulhamit Subasi;Abdulhamit Subasi

  • EEG-based driving fatigue detection using multilevel feature extraction and iterative hybrid feature selection

    Turker Tuncer;Sengul Dogan;Abdulhamit Subasi;Abdulhamit Subasi

  • Decision support system for major depression detection using spectrogram and convolution neural network with EEG signals

    Hui Wen Loh;Chui Ping Ooi;Emrah Aydemir;Turker Tuncer

  • PrimePatNet87: Prime pattern and tunable q-factor wavelet transform techniques for automated accurate EEG emotion recognition.

    Abdullah Dogan;Merve Akay;Prabal Datta Barua;Prabal Datta Barua;Mehmet Baygin

  • PatchResNet: Multiple Patch Division–Based Deep Feature Fusion Framework for Brain Tumor Classification Using MRI Images

    Unknown

  • A novel Covid-19 and Pneumonia Classification Method based on F-transform.

    Turker Tuncer;Fatih Ozyurt;Sengul Dogan;Abdulhamit Subasi;Abdulhamit Subasi

  • LEDPatNet19: Automated Emotion Recognition Model based on Nonlinear LED Pattern Feature Extraction Function using EEG Signals

    Turker Tuncer;Sengul Dogan;Abdulhamit Subasi;Abdulhamit Subasi

  • Automated brain disease classification using exemplar deep features

    Unknown

  • A dynamic center and multi threshold point based stable feature extraction network for driver fatigue detection utilizing EEG signals

    Turker Tuncer;Sengul Dogan;Fatih Ertam;Abdulhamit Subasi

  • Tetromino pattern based accurate EEG emotion classification model

    Turker Tuncer;Sengul Dogan;Mehmet Baygin;U. Rajendra Acharya;U. Rajendra Acharya;U. Rajendra Acharya

  • A novel octopus based Parkinson’s disease and gender recognition method using vowels

    Turker Tuncer;Sengul Dogan

  • Automated arrhythmia detection with homeomorphically irreducible tree technique using more than 10,000 individual subject ECG records

    Mehmet Baygin;Türker Tuncer;Sengül Dogan;Ru San Tan

  • A new data hiding method based on chaos embedded genetic algorithm for color image

    Şengül Doğan

Frequent Co-Authors

Turker Tuncer
Turker Tuncer Fırat University
U. Rajendra Acharya
U. Rajendra Acharya University of Southern Queensland
Abdulhamit Subasi
Abdulhamit Subasi Effat University
Moloud Abdar
Moloud Abdar Deakin University
Ganesh R. Naik
Ganesh R. Naik Flinders University
N. Arunkumar
N. Arunkumar SASTRA University
Oliver Faust
Oliver Faust Sheffield Hallam University

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