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Engineering and Technology
UK
2026

D-Index & Metrics

Medicine

D-Index
106
Citations
41609
World Ranking
6536
National Ranking
631

Engineering and Technology

D-Index
101
Citations
38025
World Ranking
140
National Ranking
9

Joseph V. Hajnal publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Joseph V. Hajnal sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 581 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Joseph V. Hajnal D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Joseph V. Hajnal sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 101 D-Index — 99th percentile

99% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Engineering and Technology in United Kingdom Leader Award
  • 2020 - Fellow of the Royal Academy of Engineering (UK)

Overview

Joseph V. Hajnal is affiliated with King's College London in the United Kingdom. Their research primarily focuses on the field of Medicine, with significant contributions in subfields such as Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health, Cognitive Neuroscience, Epidemiology, and Biomedical Engineering.

The main topics covered in their work include:

  • Fetal and Pediatric Neurological Disorders
  • Advanced MRI Techniques and Applications
  • Neonatal and fetal brain pathology
  • Advanced Neuroimaging Techniques and Applications
  • Functional Brain Connectivity Studies
  • MRI in cancer diagnosis
  • Prenatal Screening and Diagnostics

Joseph V. Hajnal has published extensively in a range of scientific venues, with the most frequent publication outlets being:

  • 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
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Magnetic Resonance in Medicine
  • arXiv (Cornell University)
  • Medical Image Analysis

Among their recent papers are:

  • "A Novel Ultrasound Robot With Force/Torque Measurement and Control for Safe and Efficient Scanning" (2023) published in IEEE Transactions on Instrumentation and Measurement
  • "The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity" (2021) published in Brain
  • "The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants" (2020) published in NeuroImage
  • "The Developing Human Connectome Project Neonatal Data Release" (2022) published in Frontiers in Neuroscience
  • "Development of human white matter pathways in utero over the second and third trimester" (2021) published in Proceedings of the National Academy of Sciences

Throughout their career, Joseph V. Hajnal has frequently collaborated with several co-authors including:

  • Mary Rutherford
  • Jana Hutter
  • A. David Edwards
  • Anthony N. Price
  • Lucilio Cordero-Grande

They have been recognized as a Fellow of the Royal Academy of Engineering in the United Kingdom since 2020.

Best Publications

  • Area V5 of the Human Brain: Evidence from a Combined Study Using Positron Emission Tomography and Magnetic Resonance Imaging

    J. D. G. Watson;R. Myers;R. S. J. Frackowiak;J. V. Hajnal

  • A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction

    Jo Schlemper;Jose Caballero;Joseph V. Hajnal;Anthony N. Price

  • Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy

    Paul Aljabar;Rolf A. Heckemann;Alexander Hammers;Joseph V. Hajnal

  • Automatic anatomical brain MRI segmentation combining label propagation and decision fusion.

    Rolf A. Heckemann;Joseph V. Hajnal;Paul Aljabar;Daniel Rueckert

  • Microstructured Magnetic Materials for RF Flux Guides in Magnetic Resonance Imaging

    M. C. K. Wiltshire;J. B. Pendry;I. R. Young;D. J. Larkman

  • Use of multicoil arrays for separation of signal from multiple slices simultaneously excited.

    David J. Larkman;Joseph V. Hajnal;Amy H. Herlihy;Glyn A. Coutts

  • Artifacts due to stimulus correlated motion in functional imaging of the brain

    Joseph V. Hajnal;Ralph Myers;Angela Oatridge;Jane E. Schwieso

  • Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction

    Chen Qin;Jo Schlemper;Jose Caballero;Anthony N. Price

  • The Developing Human Connectome Project: a Minimal Processing Pipeline for Neonatal Cortical Surface Reconstruction

    Antonios Makropoulos;Emma C. Robinson;Emma C. Robinson;Andreas Schuh;Robert Wright

  • Natural history of brain lesions in extremely preterm infants studied with serial magnetic resonance imaging from birth and neurodevelopmental assessment.

    Leigh E. Dyet;Nigel Kennea;Serena J. Counsell;Elia F. Maalouf

  • MR of the brain using fluid-attenuated inversion recovery (FLAIR) pulse sequences.

    B De Coene;J V Hajnal;P Gatehouse;D B Longmore

  • Use of fluid attenuated inversion recovery (FLAIR) pulse sequences in MRI of the brain

    Joseph V. Hajnal;David J. Bryant;Larry Kasuboski;Pradip M. Pattany

  • Reconstruction of fetal brain MRI with intensity matching and complete outlier removal.

    Maria Kuklisova-Murgasova;Gerardine Quaghebeur;Mary A. Rutherford;Joseph V. Hajnal

  • Abnormal Cortical Development after Premature Birth Shown by Altered Allometric Scaling of Brain Growth

    Olga Kapellou;Serena J Counsell;Nigel Kennea;Leigh Dyet

  • Diffusion-weighted imaging of the brain in preterm infants with focal and diffuse white matter abnormality.

    Serena J Counsell;Joanna M Allsop;Michael C Harrison;David J Larkman

  • DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks

    Martin Rajchl;Matthew C. H. Lee;Ozan Oktay;Konstantinos Kamnitsas

  • Diffeomorphic registration using b-splines

    Daniel Rueckert;Paul Aljabar;Rolf A. Heckemann;Joseph V. Hajnal

  • Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain

    Antonios Makropoulos;Ioannis S Gousias;Christian Ledig;Paul Aljabar

  • Magnetic resonance imaging of total body fat

    E.L. Thomas;N. Saeed;J.V. Hajnal;A.E. Brynes

  • A registration and interpolation procedure for subvoxel matching of serially acquired MR images.

    Joseph V. Hajnal;Nadeem Saeed;Elaine J. Soar;Angela Oatridge

  • A robust method to estimate the intracranial volume across MRI field strengths (1.5T and 3T)

    Shiva Keihaninejad;Rolf A. Heckemann;Gianlorenzo Fagiolo;Mark R. Symms

Frequent Co-Authors

Daniel Rueckert
Daniel Rueckert Technical University of Munich
Mary A. Rutherford
Mary A. Rutherford King's College London
Serena J. Counsell
Serena J. Counsell King's College London
A. David Edwards
A. David Edwards King's College London
Paul Aljabar
Paul Aljabar King's College London
Graeme M. Bydder
Graeme M. Bydder University of California, San Diego
Derek L. G. Hill
Derek L. G. Hill Panoramic Digital Health
Bernhard Kainz
Bernhard Kainz Imperial College London
Alexander Hammers
Alexander Hammers King's College London
Jonathan O'Muircheartaigh
Jonathan O'Muircheartaigh King's College London

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