World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
5248
World Ranking
10844
National Ranking
4514

Mingyuan Zhou 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 Mingyuan Zhou 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: 162 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

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

Mingyuan Zhou 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 Mingyuan Zhou 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Mingyuan Zhou is affiliated with The University of Texas at Austin in the United States. Their research primarily spans the field of Computer Science, with a particular focus on subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Signal Processing, and Civil and Structural Engineering.

The scientist's work addresses multiple key topics within these disciplines. These include:

  • Domain Adaptation and Few-Shot Learning
  • Topic Modeling
  • Generative Adversarial Networks and Image Synthesis
  • Multimodal Machine Learning Applications
  • Machine Learning and Data Classification
  • Gaussian Processes and Bayesian Inference
  • Advanced Graph Neural Networks

Mingyuan Zhou has contributed extensively to the academic literature with 200 publications in Computer Science. Their frequent publication venues include:

  • arXiv (Cornell University)
  • PubMed
  • IEEE Transactions on Signal Processing
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • International Journal of Biological Macromolecules

Selected recent papers demonstrate their involvement in diverse topics and methodologies, including generative models, signal processing, and biomedical research. Examples include:

  • "Diffusion-GAN: Training GANs with Diffusion," 2022, arXiv (Cornell University)
  • "Variational Temporal Deep Generative Model for Radar HRRP Target Recognition," 2020, IEEE Transactions on Signal Processing
  • "A mixture-density-based tandem optimization network for on-demand inverse design of thin-film high reflectors," 2021, Nanophotonics
  • "Disease Burden and Attributable Risk Factors of Alzheimer's Disease and Dementia in China from 1990 to 2019," 2022, The Journal of Prevention of Alzheimer's Disease
  • "Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning," 2022, arXiv (Cornell University)

Collaboration is also a notable aspect of Zhou's research profile. Frequent coauthors include Huangjie Zheng, Bo Chen, Shujian Zhang, Weizhu Chen, and Zhendong Wang. The collaboration counts with these researchers range from 10 to 23 joint works, indicating sustained partnerships.

Best Publications

  • Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images

    Mingyuan Zhou;Haojun Chen;John Paisley;Lu Ren

  • Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations

    Mingyuan Zhou;Haojun Chen;Lu Ren;Guillermo Sapiro

  • Beta-Negative Binomial Process and Poisson Factor Analysis

    Mingyuan Zhou;Lauren A. Hannah;David B. Dunson;Lawrence Carin

  • Negative Binomial Process Count and Mixture Modeling

    Mingyuan Zhou;Lawrence Carin

  • Masking: A New Perspective of Noisy Supervision

    Bo Han;Jiangchao Yao;Gang Niu;Mingyuan Zhou

  • Infinite edge partition models for overlapping community detection and link prediction

    Mingyuan Zhou

  • Dictionary Learning for Noisy and Incomplete Hyperspectral Images

    Zhengming Xing;Mingyuan Zhou;Alexey Castrodad;Guillermo Sapiro

  • Lognormal and Gamma Mixed Negative Binomial Regression

    Mingyuan Zhou;Lingbo Li;Lawrence Carin;David B. Dunson

  • Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

    Unknown

  • Adversarially Adaptive Normalization for Single Domain Generalization

    Xinjie Fan;Qifei Wang;Junjie Ke;Feng Yang

  • Meta-Learning without Memorization

    Mingzhang Yin;George Tucker;Mingyuan Zhou;Sergey Levine

  • Lognormal and Gamma Mixed Negative Binomial Regression

    Mingyuan Zhou;Lingbo Li;David Dunson;Lawrence Carin

  • A Bayesian Nonparametric Approach to Image Super-Resolution

    Gungor Polatkan;Mingyuan Zhou;Lawrence Carin;David Blei

  • Dependent Hierarchical Beta Process for Image Interpolation and Denoising

    Mingyuan Zhou;Hongxia Yang;Guillermo Sapiro;David B. Dunson

  • Semi-Implicit Variational Inference

    Mingzhang Yin;Mingyuan Zhou

  • Augmentable gamma belief networks

    Mingyuan Zhou;Yulai Cong;Bo Chen

  • Variational Graph Recurrent Neural Networks

    Ehsan Hajiramezanali;Arman Hasanzadeh;Nick Duffield;Krishna R Narayanan

  • Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices

    Ayan Acharya;Joydeep Ghosh;Mingyuan Zhou

  • WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling

    Hao Zhang;Bo Chen;Dandan Guo;Mingyuan Zhou

  • Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

    Estee Y Cramer;Evan L Ray;Velma K Lopez;Johannes Bracher

  • Semi-Implicit Graph Variational Auto-Encoders

    Arman Hasanzadeh;Ehsan Hajiramezanali;Krishna R. Narayanan;Nick Duffield

  • Bayesian Graph Neural Networks with Adaptive Connection Sampling

    Arman Hasanzadeh;Ehsan Hajiramezanali;Shahin Boluki;Nick Duffield

Frequent Co-Authors

Bo Chen
Bo Chen Xidian University
Lawrence Carin
Lawrence Carin Duke University
David B. Dunson
David B. Dunson Duke University
Hanna Wallach
Hanna Wallach Microsoft (United States)
Krishna R. Narayanan
Krishna R. Narayanan Texas A&M University
Guillermo Sapiro
Guillermo Sapiro Princeton University
Nick Duffield
Nick Duffield Texas A&M University
Wray Buntine
Wray Buntine VinUniversity
David M. Blei
David M. Blei Columbia University
Joydeep Ghosh
Joydeep Ghosh The University of Texas at Austin

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