World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
8651
World Ranking
6209
National Ranking
821

Yue M. Lu 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 Yue M. Lu 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: 305 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Yue M. Lu 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 Yue M. Lu 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: 48 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Overview

Yue M. Lu is affiliated with Beijing University of Posts and Telecommunications in China. Their research spans several fields, primarily within computer science and mathematics, with a focus on topics related to high-dimensional learning, random matrices, and computational techniques.

Their publication record includes work in prominent venues such as arXiv (Cornell University), IEEE Transactions on Information Theory, Journal of Statistical Mechanics Theory and Experiment, SSRN Electronic Journal, and Journal of Separation Science.

Frequent coauthors collaborating with Yue M. Lu include Florent Krząkała, Lenka Zdeborová, Hong Hu, Rishabh Dudeja, and Subhabrata Sen.

Their main fields of study encompass:

  • Computer Science
  • Mathematics

Within these fields, they have contributed notably to subfields including:

  • Artificial Intelligence
  • Statistics and Probability
  • Computational Mechanics
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Yue M. Lu's research topics cover a range of areas such as:

  • Sparse and Compressive Sensing Techniques
  • Random Matrices and Applications
  • Markov Chains and Monte Carlo Methods
  • Stochastic Gradient Optimization Techniques
  • Theoretical and Computational Physics
  • Neural Networks and Applications
  • Machine Learning and ELM

Some of their recent papers include:

  • "Universality Laws for High-Dimensional Learning With Random Features," 2022, IEEE Transactions on Information Theory
  • "Preparation of hydrophilic molecularly imprinted solid-phase microextraction fiber for the selective removal and extraction of trace tetracyclines residues in animal derived foods," 2020, Journal of Separation Science
  • "The role of regularization in classification of high-dimensional noisy Gaussian mixture," 2020, arXiv (Cornell University)
  • "Universality of approximate message passing with semirandom matrices," 2023, The Annals of Probability
  • "Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization," 2020, arXiv (Cornell University)

Best Publications

  • Supervised and Traditional Term Weighting Methods for Automatic Text Categorization

    Man Lan;Chew Lim Tan;Jian Su;Yue Lu

  • An Algorithm for License Plate Recognition Applied to Intelligent Transportation System

    Ying Wen;Yue Lu;Jingqi Yan;Zhenyu Zhou

  • Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview

    Yuejie Chi;Yue M. Lu;Yuxin Chen

  • A Theory for Sampling Signals From a Union of Subspaces

    Y.M. Lu;M.N. Do

  • Acoustic echoes reveal room shape

    Ivan Dokmanić;Reza Parhizkar;Andreas Walther;Yue M. Lu

  • Multidimensional Directional Filter Banks and Surfacelets

    Y.M. Lu;M.N. Do

  • A New Contourlet Transform with Sharp Frequency Localization

    Y. Lu;M. N. Do

  • A Spectral Graph Uncertainty Principle

    A. Agaskar;Y. M. Lu

  • Multilingual scene character recognition with co-occurrence of histogram of oriented gradients

    Shangxuan Tian;Ujjwal Bhattacharya;Shijian Lu;Bolan Su

  • Handwritten Bangla numeral recognition system and its application to postal automation

    Ying Wen;Yue Lu;Pengfei Shi

  • A nearest-neighbor chain based approach to skew estimation in document images

    Yue Lu;Chew Lim Tan

  • Bits From Photons: Oversampled Image Acquisition Using Binary Poisson Statistics

    Feng Yang;Y. M. Lu;L. Sbaiz;M. Vetterli

  • Bangla/English script identification based on analysis of connected component profiles

    Lijun Zhou;Yue Lu;Chew Lim Tan

  • DG-Font: Deformable Generative Networks for Unsupervised Font Generation

    Yangchen Xie;Xinyuan Chen;Li Sun;Yue Lu

  • Can one hear the shape of a room: The 2-D polygonal case

    Ivan Dokmanic;Yue M. Lu;Martin Vetterli

  • An approach to word image matching based on weighted Hausdorff distance

    Yue Lu;Chew Lim Tan;Weihua Huang;Liying Fan

  • Designing color filter arrays for the joint capture of visible and near-infrared images

    Yue M. Lu;Clement Fredembach;Martin Vetterli;Sabine Susstrunk

  • A Distributed Gauss-Newton Method for Power System State Estimation

    Ariana Minot;Yue M. Lu;Na Li

  • Monte Carlo non-local means: random sampling for large-scale image filtering.

    Stanley H. Chan;Todd E. Zickler;Yue M. Lu

  • Streaming PCA and Subspace Tracking: The Missing Data Case

    Laura Balzano;Yuejie Chi;Yue M. Lu

  • Image interpolation using multiscale geometric representations

    Nickolaus Mueller;Yue M. Lu;Minh N. Do

  • CRISP contourlets: a critically sampled directional multiresolution image representation

    Yue Lu;Minh N. Do

  • Universality Laws for High-Dimensional Learning with Random Features.

    Hong Hu;Yue M. Lu

Frequent Co-Authors

Martin Vetterli
Martin Vetterli École Polytechnique Fédérale de Lausanne
Chew Lim Tan
Chew Lim Tan National University of Singapore
Minh N. Do
Minh N. Do University of Illinois at Urbana-Champaign
Sabine Süsstrunk
Sabine Süsstrunk École Polytechnique Fédérale de Lausanne
Ching Y. Suen
Ching Y. Suen Concordia University
Pier Luigi Dragotti
Pier Luigi Dragotti Imperial College London
Todd Zickler
Todd Zickler Harvard University
Shiliang Sun
Shiliang Sun East China Normal University
Lenka Zdeborová
Lenka Zdeborová École Polytechnique Fédérale de Lausanne
Florent Krzakala
Florent Krzakala École Polytechnique Fédérale de Lausanne

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