World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
75
Citations
25837
World Ranking
1401
National Ranking
82

Anima Anandkumar 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 Anima Anandkumar 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: 361 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Anima Anandkumar 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 Anima Anandkumar 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: 75 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Overview

Anima Anandkumar is affiliated with Nvidia in the United Kingdom and has contributed extensively to research at the intersection of computer science and medicine. Their work encompasses various subfields, including artificial intelligence, computer vision and pattern recognition, surgery, biomedical engineering, and health informatics.

Their recent publications demonstrate a focus on AI-driven methods applied to medical and surgical contexts, as well as advances in machine learning models. Notable papers include:

  • "FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators" (2022, arXiv (Cornell University))
  • "A vision transformer for decoding surgeon activity from surgical videos" (2023, Nature Biomedical Engineering)
  • "Convolutional Tensor-Train LSTM for Spatio-temporal Learning" (2020, arXiv (Cornell University))
  • "A multi-institutional study using artificial intelligence to provide reliable and fair feedback to surgeons" (2023, Communications Medicine)
  • "Surgical gestures as a method to quantify surgical performance and predict patient outcomes" (2022, npj Digital Medicine)

Anandkumar has collaborated frequently with several researchers, including Andrew J. Hung, Daniel A. Donoho, Yuke Zhu, Dani Kiyasseh, and Dhiraj J. Pangal. These co-authors appear regularly in their research publications, indicating ongoing partnerships within related domains.

Their work has been disseminated primarily through specific venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • npj Digital Medicine
  • The Journal of Urology
  • Nature Biomedical Engineering

The main fields of study covered by Anandkumar include computer science with 45 publications and medicine with 40. Within these, their research targets several subfields:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Surgery
  • Biomedical Engineering
  • Health Informatics

Research topics across their portfolio concentrate on areas such as:

  • Surgical Simulation and Training
  • Artificial Intelligence in Healthcare and Education
  • Machine Learning in Materials Science
  • Anatomy and Medical Technology
  • History and Advancements in Chemistry
  • Cardiac, Anesthesia and Surgical Outcomes
  • Advanced Vision and Imaging

Best Publications

  • SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

    Enze Xie;Wenhai Wang;Zhiding Yu;Anima Anandkumar

  • Fourier Neural Operator for Parametric Partial Differential Equations

    Zongyi Li;Nikola Borislavov Kovachki;Kamyar Azizzadenesheli;Burigede liu

  • Tensor decompositions for learning latent variable models

    Animashree Anandkumar;Rong Ge;Daniel Hsu;Sham M. Kakade

  • Born Again Neural Networks

    Tommaso Furlanello;Zachary Chase Lipton;Michael Tschannen;Laurent Itti

  • Physics-informed machine learning: case studies for weather and climate modelling.

    K. Kashinath;M. Mustafa;A. Albert;J. L. Wu;J. L. Wu

  • Deep Active Learning for Named Entity Recognition.

    Yanyao Shen;Hyokun Yun;Zachary C. Lipton;Yakov Kronrod

  • signSGD: Compressed Optimisation for Non-Convex Problems

    Jeremy Bernstein;Yu-Xiang Wang;Kamyar Azizzadenesheli;Animashree Anandkumar

  • U-FNO - an enhanced Fourier neural operator based-deep learning model for multiphase flow.

    Gege Wen;Zongyi Li;Kamyar Azizzadenesheli;Anima Anandkumar

  • Neural Operator: Graph Kernel Network for Partial Differential Equations

    Zongyi Li;Nikola B. Kovachki;Kamyar Azizzadenesheli;Burigede Liu

  • Stochastic Activation Pruning for Robust Adversarial Defense

    Guneet S. Dhillon;Kamyar Azizzadenesheli;Zachary C. Lipton;Jeremy D. Bernstein

  • Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret

    A Anandkumar;N Michael;A K Tang;A Swami

  • A Method of Moments for Mixture Models and Hidden Markov Models

    Animashree Anandkumar;Daniel J. Hsu;Sham M. Kakade

  • TensorLy: tensor learning in python

    Jean Kossaifi;Yannis Panagakis;Anima Anandkumar;Maja Pantic

  • Neural Lander: Stable Drone Landing Control Using Learned Dynamics

    Guanya Shi;Xichen Shi;Michael O'Connell;Rose Yu

  • A Tensor Spectral Approach to Learning Mixed Membership Community Models

    Animashree Anandkumar;Rong Ge;Daniel J. Hsu;Sham M. Kakade

  • Learning Latent Tree Graphical Models

    Myung Jin Choi;Vincent Y. F. Tan;Animashree Anandkumar;Alan S. Willsky

  • A Spectral Algorithm for Latent Dirichlet Allocation

    Animashree Anandkumar;Dean P. Foster;Daniel Hsu;Sham M. Kakade

  • Beating the Perils of Non-Convexity: Guaranteed Training of Neural Networks using Tensor Methods

    Majid Janzamin;Hanie Sedghi;Anima Anandkumar

  • OrbNet: Deep learning for quantum chemistry using symmetry-adapted atomic-orbital features.

    Zhuoran Qiao;Matthew Welborn;Animashree Anandkumar;Frederick R. Manby

  • Opportunistic Spectrum Access with Multiple Users: Learning under Competition

    Animashree Anandkumar;Nithin Michael;Ao Tang

  • Non-convex Robust PCA

    Praneeth Netrapalli;Niranjan U N;Sujay Sanghavi;Animashree Anandkumar

  • Multipole Graph Neural Operator for Parametric Partial Differential Equations

    Zongyi Li;Nikola B. Kovachki;Kamyar Azizzadenesheli;Burigede Liu

Frequent Co-Authors

Vincent Y. F. Tan
Vincent Y. F. Tan National University of Singapore
Daniel Hsu
Daniel Hsu Columbia University
Sham M. Kakade
Sham M. Kakade Harvard University
Yisong Yue
Yisong Yue California Institute of Technology
Yuke Zhu
Yuke Zhu The University of Texas at Austin
Rong Ge
Rong Ge Duke University
Zachary C. Lipton
Zachary C. Lipton Carnegie Mellon University
Lang Tong
Lang Tong Cornell University
Animesh Garg
Animesh Garg University of Toronto

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