World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
7068
World Ranking
8844
National Ranking
3774

Liang 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 Liang 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: 117 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

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

Liang 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 Liang 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: 41 D-Index — 40th percentile

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

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

Overview

Liang Huang is affiliated with Oregon State University in the United States. Their research spans multiple disciplines, primarily focusing on the intersection of biochemistry, genetics, molecular biology, and computer science.

The scientist has contributed extensively to the fields of biochemistry, genetics and molecular biology, with 76 publications, and computer science, with 28 publications. Within these broader fields, their work delves into specific subfields including:

  • Molecular Biology
  • Artificial Intelligence
  • Infectious Diseases
  • Animal Science and Zoology
  • Cardiology and Cardiovascular Medicine

Liang Huang's main research topics reflect interests in both biological and computational approaches:

  • RNA and protein synthesis mechanisms
  • RNA modifications and cancer
  • RNA Research and Splicing
  • Natural Language Processing Techniques
  • Topic Modeling
  • RNA Interference and Gene Delivery
  • Animal Virus Infections Studies

The scientist has coauthored many papers with several frequent collaborators, indicating sustained research partnerships. These coauthors include:

  • David H. Mathews (25 coauthored papers)
  • He Zhang (17 coauthored papers)
  • Liang Zhang (15 coauthored papers)
  • Sizhen Li (15 coauthored papers)
  • Tianshuo Zhou (8 coauthored papers)

Liang Huang's publications appear predominantly in venues such as:

  • arXiv (Cornell University) with 13 publications
  • bioRxiv (Cold Spring Harbor Laboratory) with 5 publications
  • Bioinformatics with 3 publications
  • SSRN Electronic Journal with 3 publications
  • Nucleic Acids Research with 2 publications

Some recent papers authored or coauthored by Liang Huang include:

  • "Comparative multiomics analyses reveal the breed effect on the colonic host-microbe interactions in pig" (2024, iMetaOmics.)
  • "Algorithm for optimized mRNA design improves stability and immunogenicity" (2023, Nature)
  • "Generation and Functional Analysis of Defective Viral Genomes during SARS-CoV-2 Infection" (2023, mBio)
  • "LinearPartition: linear-time approximation of RNA folding partition function and base-pairing probabilities" (2020, Bioinformatics)
  • "CoV-Seq, a New Tool for SARS-CoV-2 Genome Analysis and Visualization: Development and Usability Study" (2020, Journal of Medical Internet Research)

Best Publications

  • Joint Event Extraction via Structured Prediction with Global Features

    Qi Li;Heng Ji;Liang Huang

  • Better k-best Parsing

    Liang Huang;David Chiang

  • Forest Rescoring: Faster Decoding with Integrated Language Models

    Liang Huang;David Chiang

  • Forest Reranking: Discriminative Parsing with Non-Local Features

    Liang Huang

  • Dynamic Programming for Linear-Time Incremental Parsing

    Liang Huang;Kenji Sagae

  • Atomic engineering of single-atom nanozymes for enzyme-like catalysis

    Weiwei Wu;Liang Huang;Liang Huang;Erkang Wang;Erkang Wang;Shaojun Dong;Shaojun Dong

  • bpRNA: large-scale automated annotation and analysis of RNA secondary structure.

    Padideh Danaee;Mason Rouches;Michelle Wiley;Dezhong Deng

  • Statistical syntax-directed translation with extended domain of locality

    Liang Huang;Kevin Knight;Aravind Joshi

  • LinearFold: linear-time approximate RNA folding by 5'-to-3' dynamic programming and beam search.

    Liang Huang;Liang Huang;He Zhang;Dezhong Deng;Kai Zhao

  • Forest-Based Translation

    Haitao Mi;Liang Huang;Qun Liu

  • Structured Perceptron with Inexact Search

    Liang Huang;Suphan Fayong;Yang Guo

  • STACL: Simultaneous Translation with Implicit Anticipation and Controllable Latency using Prefix-to-Prefix Framework

    Mingbo Ma;Liang Huang;Hao Xiong;Renjie Zheng

  • Structure-aware Interactive Graph Neural Networks for the Prediction of Protein-Ligand Binding Affinity

    Shuangli Li;Jingbo Zhou;Tong Xu;Liang Huang

  • Progress in Machine Translation

    Haifeng Wang;Hua Wu;Zhongjun He;Liang Huang

  • Synchronous Binarization for Machine Translation

    Hao Zhang;Liang Huang;Daniel Gildea;Kevin Knight

  • Dependency-based Convolutional Neural Networks for Sentence Embedding

    Mingbo Ma;Liang Huang;Bowen Zhou;Bing Xiang

  • Forest-based Translation Rule Extraction

    Haitao Mi;Liang Huang

  • A Cascaded Linear Model for Joint Chinese Word Segmentation and Part-of-Speech Tagging

    Wenbin Jiang;Liang Huang;Qun Liu;Yajuan L"u

  • Span-Based Constituency Parsing with a Structure-Label System and Provably Optimal Dynamic Oracles.

    James Cross;Liang Huang

  • Self-dissociation-assembly of ultrathin metal-organic framework nanosheet arrays for efficient oxygen evolution

    Liang Huang;Liang Huang;Ge Gao;Ge Gao;He Zhang;He Zhang;Jinxing Chen;Jinxing Chen

  • Dependency-based Convolutional Neural Networks for Sentence Embedding

    Mingbo Ma;Liang Huang;Bing Xiang;Bowen Zhou

Frequent Co-Authors

Shaojun Dong
Shaojun Dong Chinese Academy of Sciences
David H. Mathews
David H. Mathews University of Rochester Medical Center
Qun Liu
Qun Liu Huawei Technologies (China)
Kenneth Church
Kenneth Church Baidu (China)
Bing Xiang
Bing Xiang Amazon (United States)
Bowen Zhou
Bowen Zhou IBM (United States)
Kevin Knight
Kevin Knight University of Southern California
Haifeng Wang
Haifeng Wang Baidu (China)
Hua Wu
Hua Wu Baidu (China)
Daniel Gildea
Daniel Gildea University of Rochester

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