World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
8431
World Ranking
7553
National Ranking
3283

Yufei Huang 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 Yufei Huang 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: 262 publications — 65th percentile

65% of scientists in this discipline score the same or lower.

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

Yufei Huang 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 Yufei Huang 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.

Overview

Yufei Huang is affiliated with the University of Pittsburgh in the United States. Their research primarily focuses on the intersection of molecular biology, oncology, and artificial intelligence, with a significant emphasis on biochemistry, genetics, and molecular biology overall.

The main fields of study Huang works in include:

  • Biochemistry, Genetics and Molecular Biology

Their work spans multiple subfields such as:

  • Molecular Biology
  • Oncology
  • Artificial Intelligence
  • Materials Chemistry
  • Plant Science

The scientist investigates specific topics detailed as:

  • RNA modifications and cancer
  • Bioinformatics and Genomic Networks
  • Cancer-related molecular mechanisms research
  • Machine Learning in Bioinformatics
  • Viral-associated cancers and disorders
  • Advanced Photocatalysis Techniques
  • Computational Drug Discovery Methods

Huang's recent publications include:

  • "Convolutional neural network models for cancer type prediction based on gene expression," 2020, BMC Medical Genomics
  • "Classification of Cancer Types Using Graph Convolutional Neural Networks," 2020, Frontiers in Physics
  • "M6A RNA Methylation Regulates Histone Ubiquitination to Support Cancer Growth and Progression," 2022, Cancer Research
  • "Efficiency of Traditional Chinese medicine targeting the Nrf2/HO-1 signaling pathway," 2020, Biomedicine & Pharmacotherapy
  • "Dynamics analysis and wear prediction of rigid-flexible coupling deployable solar array system with clearance joints considering solid lubrication," 2021, Mechanical Systems and Signal Processing

Frequent co-authors collaborating with Huang are:

  • Shou-Jiang Gao
  • Yu-Chiao Chiu
  • Yidong Chen
  • Stan Z. Li
  • Luping Chen

Contributions have been published mainly in venues such as:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • SSRN Electronic Journal
  • Cancer Research
  • Journal of Medical Virology

Best Publications

  • Particle filtering

    P.M. Djuric;J.H. Kotecha;Jianqui Zhang;Yufei Huang

  • Prediction of microRNAs Associated with Human Diseases Based on Weighted k Most Similar Neighbors

    Ping Xuan;Ke Han;Maozu Guo;Yahong Guo

  • Convolutional neural network models for cancer type prediction based on gene expression

    Milad Mostavi;Milad Mostavi;Yu Chiao Chiu;Yufei Huang;Yufei Huang;Yidong Chen;Yidong Chen

  • Accurate EEG-Based Emotion Recognition on Combined Features Using Deep Convolutional Neural Networks

    Jingxia Chen;P. W. Zhang;Z. J. Mao;Y. F. Huang

  • Predicting drug response of tumors from integrated genomic profiles by deep neural networks

    Yu Chiao Chiu;Hung I.Harry Chen;Hung I.Harry Chen;Tinghe Zhang;Songyao Zhang;Songyao Zhang

  • EEG-based prediction of driver's cognitive performance by deep convolutional neural network

    Mehdi Hajinoroozi;Zijing Mao;Tzyy-Ping Jung;Chin-Teng Lin

  • Survey of Computational Algorithms for MicroRNA Target Prediction

    Dong Yue;Hui Liu;Yufei Huang

  • Exome-based analysis for RNA epigenome sequencing data

    Jia Meng;Xiaodong Cui;Manjeet K. Rao;Yidong Chen

  • A Bayesian framework for the inference of gene regulatory networks from time and pseudo-time series data.

    M Sanchez-Castillo;D Blanco;I M Tienda-Luna;M C Carrion

  • Guitar: An R/Bioconductor Package for Gene Annotation Guided Transcriptomic Analysis of RNA-Related Genomic Features

    Xiaodong Cui;Zhen Wei;Lin Zhang;Hui Liu

  • Improving performance of mammalian microRNA target prediction.

    Hui Liu;Dong Yue;Yidong Chen;Shou Jiang Gao

  • Genomic signal processing.

    Edward R. Dougherty;Yufei Huang;Seungchan Kim;Xiaodong Cai

  • Classification of Cancer Types Using Graph Convolutional Neural Networks

    Ricardo Ramirez;Yu Chiao Chiu;Allen Hererra;Milad Mostavi

  • A novel algorithm for calling mRNA m6A peaks by modeling biological variances in MeRIP-seq data

    Xiaodong Cui;Jia Meng;Shaowu Zhang;Yidong Chen

  • Review of Peak Detection Algorithms in Liquid-Chromatography-Mass Spectrometry

    Jianqiu Zhang;Elias Gonzalez;Travis Hestilow;William Haskins

  • MeT-DB V2.0: elucidating context-specific functions of N6-methyl-adenosine methyltranscriptome

    Hui Liu;Huaizhi Wang;Zhen Wei;Songyao Zhang;Songyao Zhang

  • MeTDiff: A Novel Differential RNA Methylation Analysis for MeRIP-Seq Data

    Xiaodong Cui;Lin Zhang;Jia Meng;Manjeet K. Rao

  • Reconfigurable Intelligent Surfaces-Assisted Multiuser MIMO Uplink Transmission With Partial CSI

    Li You;Jiayuan Xiong;Yufei Huang;Derrick Wing Kwan Ng

  • PlantMiRNAPred: efficient classification of real and pseudo plant pre-miRNAs.

    Ping Xuan;Maozu Guo;Xiaoyan Liu;Yangchao Huang

  • EEG-based biometric identification with deep learning

    Zijing Mao;Wan Xiang Yao;Yufei Huang

  • Reverse engineering gene regulatory networks

    Yufei Huang;I. Tienda-Luna;Yufeng Wang

Frequent Co-Authors

Shou-Jiang Gao
Shou-Jiang Gao University of Pittsburgh
Hui Liu
Hui Liu China University of Mining and Technology
Petar M. Djuric
Petar M. Djuric Stony Brook University
Zhongming Zhao
Zhongming Zhao The University of Texas Health Science Center at Houston
Hua Xu
Hua Xu Yale University
Tzyy-Ping Jung
Tzyy-Ping Jung University of California, San Diego
Bing Zhang
Bing Zhang Baylor College of Medicine
Runsheng Chen
Runsheng Chen Chinese Academy of Sciences
Maozu Guo
Maozu Guo Beijing University of Civil Engineering and Architecture
Lee Cooper
Lee Cooper Northwestern University

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Related Online Degrees & Career Pathways

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