World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
9423
World Ranking
7500
National Ranking
3264

Yihong Wu 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 Yihong Wu 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: 199 publications — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Yihong Wu 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 Yihong Wu 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: 44 D-Index — 48th percentile

48% 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

  • 2018 - Fellow of Alfred P. Sloan Foundation

Overview

Yihong Wu is affiliated with Yale University in the United States and has contributed extensively to the fields of computer science and mathematics. Their research covers a broad range of topics, emphasizing artificial intelligence, statistics and probability, and computer vision and pattern recognition.

The subfields in which they have published include:

  • Artificial Intelligence
  • Statistics and Probability
  • Computer Vision and Pattern Recognition
  • Statistical and Nonlinear Physics
  • Signal Processing

Wu's work spans several main topics such as:

  • Bayesian Methods and Mixture Models
  • Statistical Methods and Inference
  • Markov Chains and Monte Carlo Methods
  • Statistical Methods and Bayesian Inference
  • Graph Theory and Algorithms
  • Random Matrices and Applications
  • Machine Learning and Algorithms

They have a significant presence in publication venues, predominantly in:

  • arXiv (Cornell University)
  • The Annals of Statistics
  • IEEE Transactions on Information Theory
  • Probability Theory and Related Fields
  • Mathematical Statistics and Learning

Among their recent papers are:

  • "Heteroskedastic PCA: Algorithm, optimality, and applications" (2022), published in The Annals of Statistics
  • "Efficient random graph matching via degree profiles" (2020), published in Probability Theory and Related Fields
  • "Optimal rates of entropy estimation over Lipschitz balls" (2020), published in The Annals of Statistics
  • "Settling the Sharp Reconstruction Thresholds of Random Graph Matching" (2022), published in IEEE Transactions on Information Theory
  • "Optimal estimation of Gaussian mixtures via denoised method of moments" (2020), published in The Annals of Statistics

Frequent collaborators in their research include:

  • Jiaming Xu
  • Yury Polyanskiy
  • Sophie H. Yu
  • Cheng Mao
  • Pengkun Yang

Wu has also authored a book titled Information Theory, published by Cambridge University Press in 2024.

In recognition of their contributions, Wu was awarded the title of Fellow of the Alfred P. Sloan Foundation in 2018.

Best Publications

  • 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

  • A deep learning model integrating FCNNs and CRFs for brain tumor segmentation.

    Xiaomei Zhao;Yihong Wu;Guidong Song;Zhenye Li

  • Sparse PCA: Optimal rates and adaptive estimation

    T. Tony Cai;Zongming Ma;Yihong Wu

  • Estimation in Gaussian Noise: Properties of the Minimum Mean-Square Error

    Dongning Guo;Yihong Wu;Shlomo Shamai;Sergio Verdú

  • Achieving Exact Cluster Recovery Threshold via Semidefinite Programming

    Bruce Hajek;Yihong Wu;Jiaming Xu

  • Minimax Rates of Entropy Estimation on Large Alphabets via Best Polynomial Approximation

    Yihong Wu;Pengkun Yang

  • Rényi Information Dimension: Fundamental Limits of Almost Lossless Analog Compression

    Yihong Wu;Sergio Verdú

  • Functional Properties of Minimum Mean-Square Error and Mutual Information

    Yihong Wu;S. Verdu

  • PnP Problem Revisited

    Yihong Wu;Zhanyi Hu

  • Optimal Estimation and Rank Detection for Sparse Spiked Covariance Matrices.

    T. Tony Cai;Zongming Ma;Yihong Wu

  • Optimal Phase Transitions in Compressed Sensing

    Yihong Wu;S. Verdu

  • Computational barriers in minimax submatrix detection

    Zongming Ma;Yihong Wu

  • Optimal prediction of the number of unseen species

    Alon Orlitsky;Ananda Theertha Suresh;Yihong Wu

  • Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions

    Bruce Hajek;Yihong Wu;Jiaming Xu

  • Strong data-processing inequalities for channels and Bayesian networks

    Yury Polyanskiy;Yihong Wu

  • Image-based camera localization: an overview

    Yihong Wu;Fulin Tang;Heping Li

  • Camera Calibration from the Quasi-affine Invariance of Two Parallel Circles

    Yihong Wu;Haijiang Zhu;Zhanyi Hu;Fuchao Wu

  • Wasserstein Continuity of Entropy and Outer Bounds for Interference Channels

    Yury Polyanskiy;Yihong Wu

  • Chebyshev polynomials, moment matching, and optimal estimation of the unseen

    Yihong Wu;Pengkun Yang

  • MMSE Dimension

    Yihong Wu;S. Verdu

  • Dissipation of Information in Channels With Input Constraints

    Yury Polyanskiy;Yihong Wu

  • Computational lower bounds for community detection on random graphs

    Bruce Hajek;Yihong Wu;Jiaming Xu

Frequent Co-Authors

Bruce Hajek
Bruce Hajek University of Illinois at Urbana-Champaign
Sergio Verdu
Sergio Verdu Princeton University
Tony Cai
Tony Cai University of Pennsylvania
Alon Orlitsky
Alon Orlitsky University of California, San Diego
Yoram Bresler
Yoram Bresler University of Illinois at Urbana-Champaign
Jianwei Huang
Jianwei Huang Chinese University of Hong Kong, Shenzhen
Dongning Guo
Dongning Guo Northwestern University
Shlomo Shamai
Shlomo Shamai Technion – Israel Institute of Technology
Tsachy Weissman
Tsachy Weissman Stanford University

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