World's Best Scientists 2026 revealed!
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Yong Fan

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 56 4004 3891 1909 1842 205 15765

Yong Fan publications per year

The chart shows the history of publications by Yong Fan between 2000 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Yong Fan published across 26 years, from 2000 to 2025, averaging 13.8 papers a year. Output peaked at 36 publications in 2018. 45 of the 358 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 2000 to 2025. Vertical axis: number of publications, 0 to 36. Peak 36 publications in 2018. 2000: 1 publication 2001: 2 publications 2002: 5 publications 2003: 1 publication 2004: 1 publication 2005: 4 publications 2006: 6 publications 2007: 4 publications 2008: 8 publications 2009: 10 publications 2010: 10 publications 2011: 5 publications 2012: 11 publications 2013: 8 publications 2014: 9 publications 2015: 9 publications 2016: 12 publications 2017: 18 publications 2018: 36 publications 2019: 30 publications 2020: 35 publications 2021: 34 publications 2022: 21 publications 2023: 33 publications 2024: 23 publications 2025: 22 publications
2000 2025

358 publications in total across all disciplines

View publications per year as a table
Yong Fan: publications per year, 2000 to 2025
Year Publications
2000 1
2001 2
2002 5
2003 1
2004 1
2005 4
2006 6
2007 4
2008 8
2009 10
2010 10
2011 5
2012 11
2013 8
2014 9
2015 9
2016 12
2017 18
2018 36
2019 30
2020 35
2021 34
2022 21
2023 33
2024 23
2025 22
Total 358
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Yong Fan 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 Yong Fan 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, 202–211 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: 205 publications — 48th percentile

48% 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
202–211 508 205
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
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

Yong Fan 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 Yong Fan 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, 56–57 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: 56 D-Index — 72nd percentile

72% 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
54–55 500
56–57 458 56
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

Yong Fan is affiliated with the University of Pennsylvania in the United States. Their research primarily spans the fields of Medicine and Neuroscience, with a significant emphasis on Cognitive Neuroscience and Radiology, Nuclear Medicine, and Imaging. Additional subfields in their work include Experimental and Cognitive Psychology, Psychiatry and Mental Health, and Computer Vision and Pattern Recognition.

Their research topics focus mainly on Functional Brain Connectivity Studies, Advanced Neuroimaging Techniques and Applications, Mental Health Research Topics, Neural Dynamics and Brain Function, Advanced MRI Techniques and Applications, Radiomics and Machine Learning in Medical Imaging, and Dementia and Cognitive Impairment Research.

Yong Fan has contributed to various scholarly works published in reputable venues. The most frequent publication venues include bioRxiv (Cold Spring Harbor Laboratory), Biological Psychiatry, arXiv (Cornell University), International Journal of Radiation Oncology*Biology*Physics, and JAMA Psychiatry.

Some of their recent papers are as follows:

  • "MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14,468 individuals worldwide" (2020) Brain
  • "Individual Variation in Functional Topography of Association Networks in Youth" (2020) Neuron
  • "Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning" (2020) Brain
  • "Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum" (2022) JAMA Neurology
  • "The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans" (2020) Alzheimer's & Dementia

Their frequent co-authors include Christos Davatzikos, Theodore D. Satterthwaite, Russell T. Shinohara, Hongming Li, and Güray Erus.

Best Publications

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • A deep learning model integrating FCNNs and CRFs for brain tumor segmentation.

    Xiaomei Zhao;Yihong Wu;Guidong Song;Zhenye Li

  • Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: Results from ADNI

    Chandan Misra;Yong Fan;Christos Davatzikos

  • Classifying spatial patterns of brain activity with machine learning methods: Application to lie detection

    Christos Davatzikos;Kosha Ruparel;Yong Fan;Dinggang Shen

  • Gender difference in neural response to psychological stress

    Jiongjiong Wang;Marc Korczykowski;Hengyi Rao;Yong Fan

  • Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline.

    Yong Fan;Nematollah Batmanghelich;Chris M. Clark;Christos Davatzikos

  • Detection of prodromal Alzheimer's disease via pattern classification of magnetic resonance imaging

    Christos Davatzikos;Yong Fan;Xiaoying Wu;Dinggang Shen

  • Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan.

    Raymond Pomponio;Guray Erus;Mohamad Habes;Jimit Doshi

  • A modified Gabor filter design method for fingerprint image enhancement

    Jianwei Yang;Lifeng Liu;Tianzi Jiang;Yong Fan

  • COMPARE: Classification of Morphological Patterns Using Adaptive Regional Elements

    Yong Fan;Dinggang Shen;R.C. Gur;R.E. Gur

  • Group information guided ICA for fMRI data analysis

    Yuhui Du;Yong Fan

  • MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide.

    Vishnu M Bashyam;Guray Erus;Jimit Doshi;Mohamad Habes

  • Structural and functional biomarkers of prodromal Alzheimer's disease: a high-dimensional pattern classification study

    Yong Fan;Susan M. Resnick;Xiaoying Wu;Christos Davatzikos

  • Individual Variation in Functional Topography of Association Networks in Youth

    Zaixu Cui;Hongming Li;Cedric H. Xia;Bart Larsen

  • Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning.

    Ganesh B Chand;Dominic B Dwyer;Guray Erus;Aristeidis Sotiras;Aristeidis Sotiras

  • Brain anatomical networks in early human brain development.

    Yong Fan;Feng Shi;Jeffrey Keith Smith;Weili Lin

  • A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data

    Hongming Li;Mohamad Habes;David A. Wolk;Yong Fan

  • Neonatal Brain Image Segmentation in Longitudinal MRI Studies

    Feng Shi;Yong Fan;Songyuan Tang;John H. Gilmore

  • High-dimensional pattern regression using machine learning: From medical images to continuous clinical variables

    Ying Wang;Yong Fan;Priyanka Bhatt;Christos Davatzikos

  • Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome

    Christos Davatzikos;Saima Rathore;Spyridon Bakas;Sarthak Pati

  • Development trends of white matter connectivity in the first years of life.

    Pew Thian Yap;Yong Fan;Yasheng Chen;John H. Gilmore

Frequent Co-Authors

Christos Davatzikos
Christos Davatzikos University of Pennsylvania
Dinggang Shen
Dinggang Shen ShanghaiTech University
Tianzi Jiang
Tianzi Jiang Chinese Academy of Sciences
Theodore D. Satterthwaite
Theodore D. Satterthwaite University of Pennsylvania
Ruben C. Gur
Ruben C. Gur University of Pennsylvania
Raquel E. Gur
Raquel E. Gur University of Pennsylvania
Daniel H. Wolf
Daniel H. Wolf University of Pennsylvania
Russell T. Shinohara
Russell T. Shinohara University of Pennsylvania
Nikolaos Koutsouleris
Nikolaos Koutsouleris Ludwig-Maximilians-Universität München
Susan M. Resnick
Susan M. Resnick National Institutes of Health

External Links

Personal website of Yong Fan Google Scholar page

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Admission requirements can be a concern for some applicants. Fortunately, there are reputable online colleges that accept 2.0 gpa, making Computer Science more accessible to non-traditional students and career changers. Additionally, studying a field like Computer Science opens doors to diverse opportunities. If you’re curious about how degrees can shape your future, consider reviewing what’s possible in a related area with what can you get with an environmental science degree for further insights into employment options and advancement.

Best Scientists Citing Yong Fan

Dinggang Shen

Dinggang Shen

ShanghaiTech University

Publications: 355

Vince D. Calhoun

Vince D. Calhoun

Georgia State University

Publications: 153

Christos Davatzikos

Christos Davatzikos

University of Pennsylvania

Publications: 126

Pew Thian Yap

Pew Thian Yap

University of North Carolina at Chapel Hill

Publications: 72

Paul M. Thompson

Paul M. Thompson

University of Southern California

Publications: 60

Jing Sui

Jing Sui

Beijing Normal University

Publications: 56

Daoqiang Zhang

Daoqiang Zhang

Nanjing University of Aeronautics and Astronautics

Publications: 55

Feng Shi

Feng Shi

United Imaging Intelligence (China)

Publications: 55

Weili Lin

Weili Lin

University of North Carolina at Chapel Hill

Publications: 49

Daniel Rueckert

Daniel Rueckert

Technical University of Munich

Publications: 43

Guorong Wu

Guorong Wu

University of North Carolina at Chapel Hill

Publications: 41

Michael W. Weiner

Michael W. Weiner

University of California, San Francisco

Publications: 37

Gang Li

Gang Li

University of North Carolina at Chapel Hill

Publications: 31

Mingxia Liu

Mingxia Liu

University of North Carolina at Chapel Hill

Publications: 30

Heung-Il Suk

Heung-Il Suk

Korea University

Publications: 30

Ruben C. Gur

Ruben C. Gur

University of Pennsylvania

Publications: 29

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