World's Best Scientists 2026 revealed!
Konstantinos Kamnitsas

Konstantinos Kamnitsas

Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
39
Citations
14168
World Ranking
678
National Ranking
37

Computer Science

D-Index
31
Citations
10644
World Ranking
13340
National Ranking
846

Konstantinos Kamnitsas 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 Konstantinos Kamnitsas 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: 105 publications — 10th percentile

10% of scientists in this discipline score the same or lower.

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

Konstantinos Kamnitsas 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 Konstantinos Kamnitsas 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: 31 D-Index — 6th percentile

6% 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

  • 2025 - Research.com Rising Stars Award

Overview

Konstantinos Kamnitsas is affiliated with the University of Oxford in the United Kingdom. Their research spans interdisciplinary fields within computer science and medicine, with a focus on artificial intelligence and medical imaging.

Their primary fields of study include:

  • Computer Science
  • Medicine

Within these domains, Kamnitsas has contributed to several subfields such as:

  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition
  • Neurology
  • Biomedical Engineering

Their main research topics encompass:

  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • COVID-19 diagnosis using AI
  • Radiomics and Machine Learning in Medical Imaging
  • Medical Image Segmentation Techniques
  • Anomaly Detection Techniques and Applications
  • Brain Tumor Detection and Classification

Kamnitsas has authored multiple recent papers published in reputable venues. Selected works include:

  • "Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI," 2022, Nature Medicine
  • "Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study," 2020, The Lancet Digital Health
  • "Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty," 2020, arXiv (Cornell University)
  • "A Review of the Metrics Used to Assess Auto-Contouring Systems in Radiotherapy," 2023, Clinical Oncology
  • "Relationship of admission blood proteomic biomarkers levels to lesion type and lesion burden in traumatic brain injury: A CENTER-TBI study," 2021, EBioMedicine

Frequent co-authors collaborating with Kamnitsas include:

  • Ben Glocker
  • F. Wagner
  • J. Alison Noble
  • Pramit Saha
  • David Menon

They have published extensively in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Medical Imaging
  • Nature Medicine
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • The Lancet Digital Health

In the area of book publications, Kamnitsas has contributed to works published by Springer Science+Business Media, including titles focused on domain adaptation, representation transfer, and healthcare AI across several years from 2020 to 2023.

Best Publications

  • Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation

    Konstantinos Kamnitsas;Christian Ledig;Virginia F.J. Newcombe;Joanna P. Simpson

  • 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

  • Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation

    Ozan Oktay;Enzo Ferrante;Konstantinos Kamnitsas;Mattias Heinrich

  • ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI

    Oskar Maier;Bjoern H. Menze;Janina von der Gablentz;Levin Häni

  • Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

    Konstantinos Kamnitsas;Konstantinos Kamnitsas;Christian F. Baumgartner;Christian Ledig;Virginia F. J. Newcombe

  • Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

    Konstantinos Kamnitsas;Wenjia Bai;Enzo Ferrante;Steven G. McDonagh

  • Domain Generalization via Model-Agnostic Learning of Semantic Features

    Qi Dou;Daniel Coelho de Castro;Konstantinos Kamnitsas;Ben Glocker

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

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

  • SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound

    Christian F. Baumgartner;Konstantinos Kamnitsas;Jacqueline Matthew;Tara P. Fletcher

  • DeepMedic for Brain Tumor Segmentation

    Konstantinos Kamnitsas;Konstantinos Kamnitsas;Enzo Ferrante;Sarah Parisot;Christian Ledig

  • Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation

    Ozan Oktay;Enzo Ferrante;Konstantinos Kamnitsas;Mattias Heinrich

  • Multi-input Cardiac Image Super-Resolution Using Convolutional Neural Networks

    Ozan Oktay;Wenjia Bai;Matthew C. H. Lee;Ricardo Guerrero

  • Evaluating reinforcement learning agents for anatomical landmark detection.

    Amir Alansary;Ozan Oktay;Yuanwei Li;Loic Le Folgoc

  • Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth

    Vanya V. Valindria;Ioannis Lavdas;Wenjia Bai;Konstantinos Kamnitsas

  • Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study

    Miguel Monteiro;Virginia F J Newcombe;Francois Mathieu;Krishma Adatia

  • Multi-scale 3D convolutional neural networks for lesion segmentation in brain MRI

    K Kamnitsas;L Chen;C Ledig;D Rueckert

  • Autofocus Layer for Semantic Segmentation

    Yao Qin;Konstantinos Kamnitsas;Siddharth Ancha;Jay Nanavati

  • Overfitting of Neural Nets Under Class Imbalance: Analysis and Improvements for Segmentation

    Zeju Li;Konstantinos Kamnitsas;Ben Glocker

  • Data Efficient Unsupervised Domain Adaptation For Cross-modality Image Segmentation

    Cheng Ouyang;Konstantinos Kamnitsas;Carlo Biffi;Jinming Duan

  • Unsupervised Lesion Detection in Brain CT using Bayesian Convolutional Autoencoders

    Nick Pawlowski;Matthew C.H. Lee;Martin Rajchl;Steven McDonagh

  • Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks

    Christian F. Baumgartner;Konstantinos Kamnitsas;Jacqueline Matthew;Sandra Smith

  • Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty

    Miguel Monteiro;Loic Le Folgoc;Daniel Coelho de Castro;Nick Pawlowski

Frequent Co-Authors

Ben Glocker
Ben Glocker Imperial College London
Daniel Rueckert
Daniel Rueckert Technical University of Munich
Bernhard Kainz
Bernhard Kainz Imperial College London
Wenjia Bai
Wenjia Bai Imperial College London
Ozan Oktay
Ozan Oktay Imperial College London
Christian Ledig
Christian Ledig University of Bamberg
David K. Menon
David K. Menon University of Cambridge
Martin Rajchl
Martin Rajchl Imperial College London
Antonio Criminisi
Antonio Criminisi Microsoft (United States)
Aditya V. Nori
Aditya V. Nori Microsoft (United States)

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