World's Best Scientists 2026 revealed!
Polina Golland

Polina Golland

D-Index & Metrics

Computer Science

D-Index
58
Citations
24695
World Ranking
3531
National Ranking
1702

Polina Golland 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 Polina Golland 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: 271 publications — 67th percentile

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

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

Polina Golland 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 Polina Golland 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: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Overview

Polina Golland is affiliated with MIT in the United States and has an extensive body of research primarily in the fields of Medicine and Computer Science. Their work integrates advanced techniques in medical imaging and computational analysis, contributing to multiple subfields such as Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Pediatrics, Perinatology and Child Health, Artificial Intelligence, and Pulmonary and Respiratory Medicine.

Their research addresses significant topics including Fetal and Pediatric Neurological Disorders, Domain Adaptation and Few-Shot Learning, Neonatal and Fetal Brain Pathology, Advanced Neuroimaging Techniques and Applications, Advanced MRI Techniques and Applications, Medical Imaging Techniques and Applications, and Medical Image Segmentation Techniques.

Polina Golland has published extensively in several prominent venues. These include:

  • arXiv (Cornell University)
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • Lecture notes in computer science
  • Stroke
  • IEEE Transactions on Medical Imaging

Frequent collaborators in Golland's work include Esra Abacı Türk, P. Ellen Grant, Elfar Adalsteinsson, Adrian V. Dalca, and Natalia S. Rost, with multiple joint publications recorded for each.

Notable recent publications by Polina Golland include:

  • "SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry" (2023, Science Advances)
  • "Computer-Aided Detection Improves Adenomas per Colonoscopy for Screening and Surveillance Colonoscopy: A Randomized Trial" (2022, Gastroenterology)
  • "Cognitive Impairment and Dementia After Stroke: Design and Rationale for the DISCOVERY Study" (2021, Stroke)
  • "NeSVoR: Implicit Neural Representation for Slice-to-Volume Reconstruction in MRI" (2023, IEEE Transactions on Medical Imaging)
  • "The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up" (2021, The Journal of Machine Learning for Biomedical Imaging)

Best Publications

  • The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

    Bjoern H. Menze;Andras Jakab;Stefan Bauer;Jayashree Kalpathy-Cramer

  • CellProfiler: image analysis software for identifying and quantifying cell phenotypes

    Anne E Carpenter;Thouis R Jones;Michael R Lamprecht;Colin Clarke

  • CellProfiler Analyst: data exploration and analysis software for complex image-based screens

    Thouis R Jones;Thouis R Jones;In Han Kang;Douglas B Wheeler;Robert A Lindquist

  • A Generative Model for Image Segmentation Based on Label Fusion

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

  • Automated segmentation of hippocampal subfields from ultra‐high resolution in vivo MRI

    Koen Van Leemput;Koen Van Leemput;Akram Bakkour;Thomas Benner;Graham Wiggins

  • Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning

    Thouis R. Jones;Thouis R. Jones;Anne E. Carpenter;Anne E. Carpenter;Michael R. Lamprecht;Jason Moffat

  • Spherical Demons: Fast Diffeomorphic Landmark-Free Surface Registration

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

  • Permutation Tests for Classification: Towards Statistical Significance in Image-Based Studies

    Polina Golland;Bruce Fischl

  • Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012

    Nicholas Ayache;Hervé Delingette;Polina Golland;Kensaku Mori

  • A generative model for brain tumor segmentation in multi- modal images

    Bjoern H. Menze;Koen Van Leemput;Danial Lashkari;Marc-André Weber

  • A distributed spatio-temporal EEG/MEG inverse solver

    Wanmei Ou;Matti S. Hämäläinen;Polina Golland

  • Voronoi-Based segmentation of cells on image manifolds

    Thouis R. Jones;Anne Carpenter;Polina Golland

  • Method for performing stereo matching to recover depths, colors and opacities of surface elements

    Richard Stephen Szeliski;Polina Golland

  • Data-driven clustering reveals a fundamental subdivision of the human cortex into two global systems

    Yulia Golland;Polina Golland;Shlomo Bentin;Rafael Malach

  • An image analysis toolbox for high-throughput C. elegans assays

    Carolina Wählby;Carolina Wählby;Lee Kamentsky;Zihan H Liu;Tammy Riklin-Raviv

  • Stereo matching with transparency and matting

    R. Szeliski;P. Golland

  • BrainPrint: a discriminative characterization of brain morphology.

    Christian Wachinger;Polina Golland;William S. Kremen;Bruce Fischl

  • SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry

    Unknown

  • Whole brain resting state functional connectivity abnormalities in schizophrenia

    Archana Venkataraman;Thomas J. Whitford;Thomas J. Whitford;Carl-Fredrik Westin;Carl-Fredrik Westin;Polina Golland

  • Stereo Matching with Transparency and Matting

    Richard Szeliski;Polina Golland

  • Permutation tests for classification

    Polina Golland;Feng Liang;Sayan Mukherjee;Dmitry Panchenko

  • CellProfiler Analyst: data exploration and analysis software for complex image-based screens

    Douglas B. Wheeler;David M. Sabatini;In Han Kang;Polina Golland

Frequent Co-Authors

Bruce Fischl
Bruce Fischl Harvard University
Christian Wachinger
Christian Wachinger Technical University of Munich
Ona Wu
Ona Wu Harvard University
Koen Van Leemput
Koen Van Leemput Harvard University
P. Ellen Grant
P. Ellen Grant Boston Children's Hospital
Jonathan Rosand
Jonathan Rosand Harvard University
Georg Langs
Georg Langs Medical University of Vienna
Braxton D. Mitchell
Braxton D. Mitchell University of Maryland, Baltimore

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