World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
64
Citations
14185
World Ranking
2637
National Ranking
1306

Deniz Erdogmus 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 Deniz Erdogmus 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: 501 publications — 93rd percentile

93% of scientists in this discipline score the same or lower.

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

Deniz Erdogmus 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 Deniz Erdogmus 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: 64 D-Index — 82nd percentile

82% of scientists in this discipline score the same or lower.

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

Overview

Deniz Erdogmus is affiliated with Northeastern University in the United States and has a substantial body of work spanning neuroscience, medicine, and computer science. Their research integrates computational methods with biomedical applications, drawing on expertise in multiple interdisciplinary fields.

Their main fields of study include:

  • Neuroscience
  • Medicine
  • Computer Science

Subfields prominently represented in their work include:

  • Cognitive Neuroscience
  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Biomedical Engineering
  • Pediatrics, Perinatology and Child Health

Deniz Erdogmus's research covers several key topics:

  • EEG and Brain-Computer Interfaces
  • Muscle activation and electromyography studies
  • Retinopathy of Prematurity Studies
  • Neonatal and fetal brain pathology
  • Neural dynamics and brain function
  • Functional Brain Connectivity Studies
  • Motor Control and Adaptation

Their recent publications include:

  • "Improving the study of brain-behavior relationships by revisiting basic assumptions," 2023, Trends in Cognitive Sciences
  • "Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging," 2020, npj Digital Medicine
  • "Learning Invariant Representations From EEG via Adversarial Inference," 2020, IEEE Access
  • "EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals," 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
  • "Comparing supervised and unsupervised approaches to emotion categorization in the human brain, body, and subjective experience," 2020, Scientific Reports

The scientist frequently publishes in venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
  • Ophthalmology Retina

Collaborations are a significant part of their work, with frequent co-authors being:

  • Tales Imbiriba
  • J. Peter Campbell
  • Michael F. Chiang
  • Susan Ostmo
  • R.V. Paul Chan

Best Publications

  • Tversky loss function for image segmentation using 3D fully convolutional deep networks

    Seyed Sadegh Mohseni Salehi;Seyed Sadegh Mohseni Salehi;Deniz Erdogmus;Ali Gholipour

  • Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks

    James M. Brown;J. Peter Campbell;Andrew Beers;Ken Chang

  • An error-entropy minimization algorithm for supervised training of nonlinear adaptive systems

    D. Erdogmus;J.C. Principe

  • The Future of Human-in-the-Loop Cyber-Physical Systems

    G. Schirner;D. Erdogmus;K. Chowdhury;T. Padir

  • Guest Editorial: Independent Component Analysis and Blind Source Separation

    Allan Kardec Barros;José Carlos Príncipe;Deniz Erdogmus

  • Generalized information potential criterion for adaptive system training

    D. Erdogmus;J.C. Principe

  • Optimizing the P300-based brain–computer interface: current status, limitations and future directions

    J N Mak;Y Arbel;J W Minett;L M McCane

  • Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging

    Seyed Sadegh Mohseni Salehi;Deniz Erdogmus;Ali Gholipour

  • Locally Defined Principal Curves and Surfaces

    Umut Ozertem;Deniz Erdogmus

  • Feature extraction using information-theoretic learning

    K.E. Hild;D. Erdogmus;K. Torkkola;J.C. Principe

  • Blind source separation using Renyi's mutual information

    K.E. Hild;D. Erdogmus;J. Principe

  • Asymmetric Loss Functions and Deep Densely Connected Networks for Highly Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection

    Seyed Raein Hashemi;Seyed Sadegh Mohseni Salehi;Deniz Erdogmus;Sanjay P. Prabhu

  • Quantitative change of EEG and respiration signals during mindfulness meditation

    Asieh Ahani;Helane Wahbeh;Hooman Nezamfar;Meghan Miller

  • Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity.

    Travis K Redd;John Peter Campbell;James M Brown;Sang Jin Kim

  • A comparison of optimal MIMO linear and nonlinear models for brain-machine interfaces.

    S. P. Kim;J. C. Sanchez;Y. N. Rao;D. Erdogmus

  • The Cauchy–Schwarz divergence and Parzen windowing: Connections to graph theory and Mercer kernels

    Robert Jenssen;Jose C. Principe;Deniz Erdogmus;Torbjørn Eltoft

  • A Novel LMS Algorithm Applied to Adaptive Noise Cancellation

    J.M. Gorriz;J. Ramirez;S. Cruces-Alvarez;C.G. Puntonet

  • Clustering using Renyi's entropy

    R. Jenssen;K.E. Hild;D. Erdogmus;J.C. Principe

  • SNR-optimality of sum-of-squares reconstruction for phased-array magnetic resonance imaging

    Erik G. Larsson;Deniz Erdogmus;Rui Yan;Jose C. Principe

  • Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the “i-ROP” System and Image Features Associated With Expert Diagnosis

    Esra Ataer-Cansizoglu;Veronica Bolon-Canedo;J. Peter Campbell;Alican Bozkurt

  • Structured Adversarial Attack: Towards General Implementation and Better Interpretability

    Kaidi Xu;Sijia Liu;Pu Zhao;Pin-Yu Chen

  • Information Theoretic Learning.

    Deniz Erdogmus;José Carlos Príncipe

Frequent Co-Authors

Jose C. Principe
Jose C. Principe University of Florida
Jayashree Kalpathy-Cramer
Jayashree Kalpathy-Cramer Harvard University
Stratis Ioannidis
Stratis Ioannidis Northeastern University
Jennifer G. Dy
Jennifer G. Dy Northeastern University
Misha Pavel
Misha Pavel Northeastern University
Robert Jenssen
Robert Jenssen University of Tromsø - The Arctic University of Norway
Dana H. Brooks
Dana H. Brooks Northeastern University
Barry Oken
Barry Oken Oregon Health & Science University
Toshiaki Koike-Akino
Toshiaki Koike-Akino Mitsubishi Electric (United States)
Ignacio Santamaria
Ignacio Santamaria University of Cantabria

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