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Mert R. Sabuncu

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 53 4714 4582 2189 2112 260 16549

Mert R. Sabuncu publications per year

The chart shows the history of publications by Mert R. Sabuncu between 2003 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Mert R. Sabuncu published across 24 years, from 2003 to 2026, averaging 14.3 papers a year. Output peaked at 35 publications in 2025. 36 of the 344 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 2003 to 2026. Vertical axis: number of publications, 0 to 35. Peak 35 publications in 2025. 2003: 2 publications 2004: 2 publications 2005: 2 publications 2006: 1 publication 2007: 5 publications 2008: 7 publications 2009: 10 publications 2010: 7 publications 2011: 5 publications 2012: 11 publications 2013: 17 publications 2014: 10 publications 2015: 14 publications 2016: 18 publications 2017: 12 publications 2018: 28 publications 2019: 28 publications 2020: 34 publications 2021: 24 publications 2022: 17 publications 2023: 26 publications 2024: 28 publications 2025: 35 publications 2026: 1 publication
2003 2026

344 publications in total across all disciplines

View publications per year as a table
Mert R. Sabuncu: publications per year, 2003 to 2026
Year Publications
2003 2
2004 2
2005 2
2006 1
2007 5
2008 7
2009 10
2010 7
2011 5
2012 11
2013 17
2014 10
2015 14
2016 18
2017 12
2018 28
2019 28
2020 34
2021 24
2022 17
2023 26
2024 28
2025 35
2026 1
Total 344
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Mert R. Sabuncu 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 Mert R. Sabuncu sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 252–261 publications, is where this scientist sits. 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
32–41 publications 991+

This scientist: 260 publications — 65th percentile

65% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377 260
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
Download as CSV

Mert R. Sabuncu 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 Mert R. Sabuncu sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 52–53 D-Index, is where this scientist sits. 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
30–31 D-Index 131+

This scientist: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518 53
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
Download as CSV

Overview

Mert R. Sabuncu is affiliated with Cornell University in the United States. Their research focuses primarily on Medicine and Computer Science, with particular attention to subfields such as Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition, and Biomedical Engineering.

Sabuncu's work covers several key topics including:

  • Advanced MRI Techniques and Applications
  • Functional Brain Connectivity Studies
  • Radiomics and Machine Learning in Medical Imaging
  • Machine Learning in Healthcare
  • Medical Imaging Techniques and Applications
  • Neural dynamics and brain function
  • Advanced Neural Network Applications

The scientist has contributed to numerous publications, with notable recent papers including:

  • "Heritability and interindividual variability of regional structure-function coupling" (2021), published in Nature Communications
  • "Deep-Learning-Based Optimization of the Under-Sampling Pattern in MRI" (2020), published in IEEE Transactions on Computational Imaging
  • "Heritability of individualized cortical network topography" (2021), published in Proceedings of the National Academy of Sciences
  • "Machine Learning Methods Predict Individual Upper-Limb Motor Impairment Following Therapy in Chronic Stroke" (2020), published in Neurorehabilitation and Neural Repair
  • "Fidelity imposed network edit (FINE) for solving ill-posed image reconstruction" (2020), published in NeuroImage

Their frequent coauthors include:

  • Amy Kuceyeski
  • Heejong Kim
  • Adrian V. Dalca
  • Alan Q. Wang
  • Keith Jamison

Sabuncu publishes extensively in several venues, particularly:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Lecture Notes in Computer Science
  • NeuroImage
  • Medical Image Analysis

Their publication record includes a strong presence in preprint repositories and journals that intersect both computational imaging and neuroscience.

Best Publications

  • The influence of head motion on intrinsic functional connectivity MRI.

    Koene R.A. Van Dijk;Mert R. Sabuncu;Mert R. Sabuncu;Randy L. Buckner

  • VoxelMorph: A Learning Framework for Deformable Medical Image Registration

    Guha Balakrishnan;Amy Zhao;Mert R. Sabuncu;John Guttag

  • Generalized cross entropy loss for training deep neural networks with noisy labels

    Zhilu Zhang;Mert R. Sabuncu

  • Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels

    Zhilu Zhang;Mert R. Sabuncu

  • Multi-Atlas Segmentation of Biomedical Images: A Survey

    Juan Eugenio Iglesias;Mert Rory Sabuncu

  • Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion.

    Ru Kong;Jingwei Li;Csaba Orban;Mert R Sabuncu

  • An Unsupervised Learning Model for Deformable Medical Image Registration

    Guha Balakrishnan;Amy Zhao;Mert R. Sabuncu;Adrian V. Dalca

  • An Unsupervised Learning Model for Deformable Medical Image Registration

    Guha Balakrishnan;Amy Zhao;Mert R. Sabuncu;John Guttag

  • A Generative Model for Image Segmentation Based on Label Fusion

    Mert R Sabuncu;B T Thomas Yeo;K Van Leemput;Bruce Fischl

  • Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models.

    Jorge L. Bernal-Rusiel;Douglas N. Greve;Martin Reuter;Bruce Fischl

  • Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces.

    Adrian V. Dalca;Adrian V. Dalca;Adrian V. Dalca;Guha Balakrishnan;John V. Guttag;Mert R. Sabuncu

  • Global signal regression strengthens association between resting-state functional connectivity and behavior

    Jingwei Li;Ru Kong;Raphaël Liégeois;Csaba Orban

  • Spherical Demons: Fast Diffeomorphic Landmark-Free Surface Registration

    B.T.T. Yeo;M.R. Sabuncu;T. Vercauteren;N. Ayache

  • Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics.

    Tong He;Ru Kong;Avram J. Holmes;Minh Nguyen

  • Neurobiological basis of head motion in brain imaging

    Ling-Li Zeng;Ling-Li Zeng;Danhong Wang;Michael D. Fox;Michael D. Fox;Mert Sabuncu

  • Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration

    Adrian V. Dalca;Guha Balakrishnan;John V. Guttag;Mert R. Sabuncu

  • Measuring and comparing brain cortical surface area and other areal quantities.

    Anderson M. Winkler;Mert R. Sabuncu;Mert R. Sabuncu;B. T. Thomas Yeo;Bruce Fischl;Bruce Fischl

  • Function-based Intersubject Alignment of Human Cortical Anatomy

    Mert R. Sabuncu;Benjamin D. Singer;Bryan Conroy;Ronald E. Bryan;Ronald E. Bryan

  • Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration

    Adrian V. Dalca;Guha Balakrishnan;John Guttag;Mert R. Sabuncu

  • Heritability and interindividual variability of regional structure-function coupling.

    Zijin Gu;Keith Wakefield Jamison;Mert Rory Sabuncu;Amy Kuceyeski

  • Clinical Prediction from Structural Brain MRI Scans: A Large-Scale Empirical Study

    Mert R. Sabuncu;Mert R. Sabuncu;Ender Konukoglu

  • Machine learning in resting-state fMRI analysis.

    Meenakshi Khosla;Keith Jamison;Gia H. Ngo;Amy Kuceyeski

  • Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data

    Jorge L. Bernal-Rusiel;Martin Reuter;Douglas N. Greve;Bruce Fischl

  • Heritability analysis with repeat measurements and its application to resting-state functional connectivity.

    Tian Ge;Avram J. Holmes;Randy L. Buckner;Jordan W. Smoller

  • Deep-Learning-Based Optimization of the Under-Sampling Pattern in MRI

    Cagla D. Bahadir;Alan Q. Wang;Adrian V. Dalca;Mert R. Sabuncu

Frequent Co-Authors

Adrian V. Dalca
Adrian V. Dalca MIT
B.T. Thomas Yeo
B.T. Thomas Yeo National University of Singapore
Yi Wang
Yi Wang Cornell University
Avram J. Holmes
Avram J. Holmes Yale University
John V. Guttag
John V. Guttag MIT
Tian Ge
Tian Ge Massachusetts General Hospital
Simon B. Eickhoff
Simon B. Eickhoff Heinrich Heine University Düsseldorf
Danilo Bzdok
Danilo Bzdok Montreal Neurological Institute and Hospital
Jordan W. Smoller
Jordan W. Smoller Harvard University
Polina Golland
Polina Golland MIT

External Links

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Graduates have many career options and can work across industries such as software development, data analysis, environmental technology, and engineering. If you are curious about pathways outside of Computer Science, check out this helpful guide on what can i do with an environmental science degree for even more ideas.

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Michael P. Milham

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Publications: 86

Jonathan Smallwood

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Publications: 75

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