World's Best Scientists 2026 revealed!

D-Index & Metrics

Medicine

D-Index
131
Citations
74259
World Ranking
2370
National Ranking
1336

Computer Science

D-Index
109
Citations
56238
World Ranking
240
National Ranking
133

Christos Davatzikos 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 Christos Davatzikos 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: 608 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Christos Davatzikos 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 Christos Davatzikos 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: 109 D-Index — 98th percentile

98% 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

  • 2016 - Fellow of the Indian National Academy of Engineering (INAE)
  • 2014 - IEEE Fellow For contributions to automatic analysis and interpretation of biomedical multi-dimensional data

Overview

Christos Davatzikos is affiliated with the University of Pennsylvania in the United States. Their research primarily focuses on advancing the field of Medicine, with significant contributions in Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Psychiatry and Mental Health, Genetics, and Molecular Biology.

Their work explores various topics including:

  • Radiomics and Machine Learning in Medical Imaging
  • Functional Brain Connectivity Studies
  • Dementia and Cognitive Impairment Research
  • Advanced Neuroimaging Techniques and Applications
  • Glioma Diagnosis and Treatment
  • Alzheimer's Disease Research and Treatments
  • Advanced MRI Techniques and Applications

Recent notable publications by Christos Davatzikos include:

  • "The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping" (2020, Radiology)
  • "Image segmentations produced by BAMF under the AIMI Annotations initiative" (2024, arXiv (Cornell University))
  • "MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14,468 individuals worldwide" (2020, Brain)
  • "Federated learning enables big data for rare cancer boundary detection" (2022, Nature Communications)
  • "QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data" (2021, Nature Methods)

Their frequent co-authors include Güray Erus, Haochang Shou, Anahita Fathi Kazerooni, Susan M. Resnick, and Russell T. Shinohara, indicating collaboration across multiple projects and studies.

Christos Davatzikos has published extensively in several venues, with the most frequent being:

  • Alzheimer's & Dementia
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Neuro-Oncology
  • arXiv (Cornell University)
  • Biological Psychiatry

Recognitions awarded to Christos Davatzikos include becoming a Fellow of the Indian National Academy of Engineering (INAE) in 2016. Additionally, they were named an IEEE Fellow in 2014 for contributions to automatic analysis and interpretation of biomedical multi-dimensional data.

Best Publications

  • The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

    Alex Zwanenburg;Alex Zwanenburg;Martin Vallières;Mahmoud A. Abdalah;Hugo J. W. L. Aerts;Hugo J. W. L. Aerts

  • Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features

    Spyridon Bakas;Hamed Akbari;Aristeidis Sotiras;Michel Bilello

  • Deformable Medical Image Registration: A Survey

    A. Sotiras;C. Davatzikos;N. Paragios

  • 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

  • Longitudinal Magnetic Resonance Imaging Studies of Older Adults: A Shrinking Brain

    Susan M. Resnick;Dzung L. Pham;Michael A. Kraut;Alan B. Zonderman

  • A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises

    S. Kevin Zhou;Hayit Greenspan;Christos Davatzikos;James S. Duncan

  • HAMMER: hierarchical attribute matching mechanism for elastic registration

    Dinggang Shen;C. Davatzikos

  • Effect of Intensive vs Standard Blood Pressure Control on Probable Dementia: A Randomized Clinical Trial.

    Jeff D. Williamson;Nicholas M. Pajewski;Alexander P. Auchus

  • Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.

    Rastko Ciric;Daniel H. Wolf;Jonathan D. Power;David R. Roalf

  • Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme.

    Evangelia I. Zacharaki;Evangelia I. Zacharaki;Sumei Wang;Sanjeev Chawla;Dong Soo Yoo;Dong Soo Yoo

  • Measurement of radiotracer concentration in brain gray matter using positron emission tomography: MRI-based correction for partial volume effects.

    Hans W. Müller-Gärtner;Jonathan M. Links;Jerry L. Prince;Robert 'Nick' Bryan

  • Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.

    Geert J. S. Litjens;Robert Toth;Wendy J. M. van de Ven;Caroline Hoeks

  • Imaging cortical association tracts in the human brain using diffusion-tensor-based axonal tracking.

    Susumu Mori;Walter E. Kaufmann;Christos Davatzikos;Bram Stieltjes

  • 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

  • Prediction of MCI to AD conversion, via MRI, CSF biomarkers, and pattern classification.

    Christos Davatzikos;Priyanka Bhatt;Leslie M. Shaw;Kayhan N. Batmanghelich

  • One-year Age Changes in MRI Brain Volumes in Older Adults

    Susan M. Resnick;Alberto F. Goldszal;Christos Davatzikos;Stephanie Golski

  • A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages

    Saima Rathore;Mohamad Habes;Muhammad Aksam Iftikhar;Amanda Shacklett

  • Longitudinal pattern of regional brain volume change differentiates normal aging from MCI

    I. Driscoll;C. Davatzikos;Y. An;X. Wu

  • Effects of intensive glucose lowering on brain structure and function in people with type 2 diabetes (ACCORD MIND): A randomised open-label substudy

    Lenore J. Launer;Michael E. Miller;Jeff D. Williamson;Ron M. Lazar

  • Neuroimaging of the Philadelphia neurodevelopmental cohort.

    Theodore D. Satterthwaite;Mark A. Elliott;Kosha Ruparel;James Loughead

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

    Christos Davatzikos;Kosha Ruparel;Yong Fan;Dinggang Shen

Frequent Co-Authors

Susan M. Resnick
Susan M. Resnick National Institutes of Health
Dinggang Shen
Dinggang Shen ShanghaiTech University
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
Russell T. Shinohara
Russell T. Shinohara University of Pennsylvania
Yong Fan
Yong Fan University of Pennsylvania
Daniel H. Wolf
Daniel H. Wolf University of Pennsylvania
Luigi Ferrucci
Luigi Ferrucci National Institutes of Health
David R. Roalf
David R. Roalf University of Pennsylvania

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