World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
4123
World Ranking
14062
National Ranking
5578

Vikas Singh 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 Vikas Singh 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: 184 publications — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Vikas Singh 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 Vikas Singh 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: 30 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Overview

Vikas Singh is affiliated with the University of Wisconsin-Madison in the United States. Their scholarly work spans primarily the fields of Medicine and Computer Science, with a significant focus on Artificial Intelligence, Genetics, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, and Surgery.

The scientist's research covers various specialized topics including:

  • Glioma Diagnosis and Treatment
  • Domain Adaptation and Few-Shot Learning
  • Adversarial Robustness in Machine Learning
  • Gaussian Processes and Bayesian Inference
  • Advanced Neuroimaging Techniques and Applications
  • Explainable Artificial Intelligence (XAI)
  • Anomaly Detection Techniques and Applications

Several of their recent publications include:

  • "Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia," 2020, Computers and Electronics in Agriculture
  • "Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention," 2021, arXiv (Cornell University)
  • "On the Versatile Uses of Partial Distance Correlation in Deep Learning," 2022, Lecture notes in computer science
  • "Alzheimer's disease genetic risk and cognitive reserve in relationship to long-term cognitive trajectories among cognitively normal individuals," 2023, Alzheimer s Research & Therapy

Vikas Singh frequently collaborates with a group of coauthors, including Rudrasis Chakraborty, Sathya N. Ravi, Aliasgar Moiyadi, Prakash Shetty, and Sridhar Epari, with multiple joint publications across their research areas.

The scientist has also contributed to published books, including one titled Computing Algorithms with Applications in Engineering, released in 2020 by Springer Nature.

Their publication record is distributed across various venues with notable contributions to:

  • arXiv (Cornell University)
  • Journal of the American College of Cardiology
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Neurology India
  • PubMed

Best Publications

  • Predictive Markers for AD in a Multi-Modality Framework: An Analysis of MCI Progression in the ADNI Population

    Chris Hinrichs;Vikas Singh;Guofan Xu;Sterling C. Johnson

  • An efficient algorithm for Co-segmentation

    Dorit S. Hochbaum;Vikas Singh

  • Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention

    Yunyang Xiong;Zhanpeng Zeng;Rudrasis Chakraborty;Mingxing Tan

  • Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset.

    Chris Hinrichs;Vikas Singh;Lopamudra Mukherjee;Guofan Xu

  • Half-integrality based algorithms for cosegmentation of images

    Lopamudra Mukherjee;Vikas Singh;Charles R Dyer

  • Gaze-enabled egocentric video summarization via constrained submodular maximization

    Jia Xu;Lopamudra Mukherjee;Yin Li;Jamieson Warner

  • Solving the multi-way matching problem by permutation synchronization

    Deepti Pachauri;Risi Kondor;Vikas Singh

  • Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia

    Arthur F.A. Fernandes;Eduardo M. Turra;Érika R. de Alvarenga;Tiago L. Passafaro

  • Scale invariant cosegmentation for image groups

    Lopamudra Mukherjee;Vikas Singh;Jiming Peng

  • MobileDets: Searching for Object Detection Architectures for Mobile Accelerators

    Yunyang Xiong;Hanxiao Liu;Suyog Gupta;Berkin Akin

  • Controlling UAVs with sensor input spoofing attacks

    Drew Davidson;Hao Wu;Robert Jellinek;Thomas Ristenpart

  • Random walks based multi-image segmentation: Quasiconvexity results and GPU-based solutions

    Maxwell D. Collins;Jia Xu;Leo Grady;Vikas Singh

  • GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity

    Jia Xu;Vamsi K. Ithapu;Lopamudra Mukherjee;James M. Rehg

  • Topology-Based Kernels With Application to Inference Problems in Alzheimer's Disease

    D. Pachauri;C. Hinrichs;M. K. Chung;S. C. Johnson

  • Extracting and summarizing white matter hyperintensities using supervised segmentation methods in Alzheimer's disease risk and aging studies.

    Vamsi Ithapu;Vikas Singh;Christopher Lindner;Benjamin P. Austin

  • Mixed Effects Neural Networks (MeNets) With Applications to Gaze Estimation

    Yunyang Xiong;Hyunwoo J. Kim;Vikas Singh

  • MKL for Robust Multi-modality AD Classification

    Chris Hinrichs;Vikas Singh;Guofan Xu;Sterling Johnson

  • Characterizing Functional Connectivity Differences in Aging Adults using Machine Learning on Resting State fMRI Data

    Svyatoslav Vergun;Alok Deshpande;Timothy B. Meier;Jie Song

  • Ensemble clustering using semidefinite programming with applications

    Vikas Singh;Lopamudra Mukherjee;Jiming Peng;Jinhui Xu

  • Imaging-based enrichment criteria using deep learning algorithms for efficient clinical trials in mild cognitive impairment

    Vamsi K. Ithapu;Vikas Singh;Ozioma C. Okonkwo;Richard J. Chappell

  • Tensorize, Factorize and Regularize: Robust Visual Relationship Learning

    Seong Jae Hwang;Hyunwoo J. Kim;Sathya N. Ravi;Maxwell D. Collins

  • 3D texture analysis for classification of second harmonic generation images of human ovarian cancer

    Bruce Wen;Bruce Wen;Kirby R. Campbell;Karissa Tilbury;Oleg Nadiarnykh

  • Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination

    Won H. Kim;Deepti Pachauri;Charles Hatt;Moo. K. Chung

  • Multivariate General Linear Models (MGLM) on Riemannian Manifolds with Applications to Statistical Analysis of Diffusion Weighted Images

    Hyunwoo J. Kim;Barbara B. Bendlin;Nagesh Adluru;Maxwell D. Collins

  • Texture analysis applied to second harmonic generation image data for ovarian cancer classification

    Bruce L. Wen;Molly A. Brewer;Oleg Nadiarnykh;James D. Hocker

  • Multi-resolution statistical analysis of brain connectivity graphs in preclinical Alzheimer's disease

    Won Hwa Kim;Nagesh Adluru;Moo K. Chung;Ozioma C. Okonkwo

  • MobileDets: Searching for Object Detection Architectures for Mobile Accelerators

    Yunyang Xiong;Hanxiao Liu;Suyog Gupta;Berkin Akin

Frequent Co-Authors

Sterling C. Johnson
Sterling C. Johnson University of Wisconsin–Madison
Moo K. Chung
Moo K. Chung University of Wisconsin–Madison
Baba C. Vemuri
Baba C. Vemuri University of Florida
Glenn Fung
Glenn Fung American Family Insurance
Rebecca L. Koscik
Rebecca L. Koscik University of Wisconsin–Madison
Ozioma C. Okonkwo
Ozioma C. Okonkwo University of Wisconsin–Madison
Sanjay Asthana
Sanjay Asthana University of Wisconsin–Madison
Andrew L. Alexander
Andrew L. Alexander University of Wisconsin–Madison
Anil K. Jain
Anil K. Jain Michigan State University
Henrik Zetterberg
Henrik Zetterberg University of Gothenburg

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