World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
78
Citations
19756
World Ranking
1221
National Ranking
168

Tianrui Li 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 Tianrui Li 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: 494 publications — 93rd percentile

93% of scientists in this discipline score the same or lower.

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

Tianrui Li 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 Tianrui Li 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: 78 D-Index — 92nd percentile

92% of scientists in this discipline score the same or lower.

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

Overview

Tianrui Li is affiliated with Southwest Jiaotong University in China and has contributed extensively to the fields of computer science and engineering. Their work spans multiple subfields, including artificial intelligence, computer vision and pattern recognition, computational theory and mathematics, information systems, and signal processing.

The scientist's research interests focus on several main topics, which include:

  • Rough Sets and Fuzzy Logic
  • Face and Expression Recognition
  • Text and Document Classification Technologies
  • Data Mining Algorithms and Applications
  • Image Retrieval and Classification Techniques
  • Traffic Prediction and Management Techniques
  • Advanced Clustering Algorithms Research

Throughout their career, Tianrui Li has published extensively across numerous venues. The most frequent publication outlets for their work are:

  • Knowledge-Based Systems
  • arXiv (Cornell University)
  • Information Sciences
  • SSRN Electronic Journal
  • Information Fusion

Some of their recent papers, reflecting their ongoing engagement with topics related to video retrieval, time series forecasting, and information fusion, include:

  • CLIP4Clip: An empirical study of CLIP for end to end video clip retrieval and captioning, 2022, Neurocomputing
  • Multivariate time series forecasting via attention-based encoder-decoder framework, 2020, Neurocomputing
  • Urban flow prediction from spatiotemporal data using machine learning: A survey, 2020, Information Fusion
  • Multi-source information fusion based on rough set theory: A review, 2020, Information Fusion
  • Long sequence time-series forecasting with deep learning: A survey, 2023, Information Fusion

Tianrui Li frequently collaborates with various researchers, with the most regular coauthors being:

  • Hongmei Chen
  • Chuan Luo
  • Shi-Jinn Horng
  • Hongjun Wang
  • Zhong Yuan

This collaboration network highlights Tianrui Li's role in a broader research community working in artificial intelligence and data mining.

Their research contributions reflect a sustained focus on both theoretical frameworks and practical applications, such as forecasting, information fusion, and pattern recognition techniques, which intersect multiple domains within computer science and engineering.

Best Publications

  • Predicting citywide crowd flows using deep spatio-temporal residual networks

    Junbo Zhang;Yu Zheng;Dekang Qi;Ruiyuan Li

  • Forecasting Fine-Grained Air Quality Based on Big Data

    Yu Zheng;Xiuwen Yi;Ming Li;Ruiyuan Li

  • Deep Air Quality Forecasting Using Hybrid Deep Learning Framework

    Shengdong Du;Tianrui Li;Yan Yang;Shi-Jinn Horng

  • Multivariate time series forecasting via attention-based encoder–decoder framework

    Shengdong Du;Tianrui Li;Yan Yang;Shi-Jinn Horng

  • A rough sets based characteristic relation approach for dynamic attribute generalization in data mining

    Tianrui Li;Da Ruan;Wets Geert;Jing Song

  • Deep Distributed Fusion Network for Air Quality Prediction

    Xiuwen Yi;Junbo Zhang;Zhaoyuan Wang;Tianrui Li

  • b-SPECS+: Batch Verification for Secure Pseudonymous Authentication in VANET

    Shi-Jinn Horng;Shiang-Feng Tzeng;Yi Pan;Pingzhi Fan

  • Urban flow prediction from spatiotemporal data using machine learning: A survey

    Peng Xie;Tianrui Li;Jia Liu;Shengdong Du

  • Enhancing Security and Privacy for Identity-Based Batch Verification Scheme in VANETs

    Shiang-Feng Tzeng;Shi-Jinn Horng;Tianrui Li;Xian Wang

  • Urban big data fusion based on deep learning: An overview

    Jia Liu;Tianrui Li;Peng Xie;Shengdong Du

  • An efficient certificateless aggregate signature with conditional privacy-preserving for vehicular sensor networks

    Shi-Jinn Horng;Shiang-Feng Tzeng;Po-Hsian Huang;Xian Wang

  • Multi-source information fusion based on rough set theory: A review

    Pengfei Zhang;Tianrui Li;Guoqiang Wang;Chuan Luo

  • Incorporating logistic regression to decision-theoretic rough sets for classifications

    Dun Liu;Tianrui Li;Decui Liang

  • A fuzzy rough set approach for incremental feature selection on hybrid information systems

    Anping Zeng;Tianrui Li;Dun Liu;Junbo Zhang

  • Three-way Investment Decisions with Decision-theoretic Rough Sets

    Dun Liu;Yiyu Yao;Tianrui Li

  • A Decision-Theoretic Rough Set Approach for Dynamic Data Mining

    Hongmei Chen;Tianrui Li;Chuan Luo;Shi-Jinn Horng

  • Probabilistic model criteria with decision-theoretic rough sets

    Dun Liu;Tianrui Li;Da Ruan

  • Composite rough sets for dynamic data mining

    Junbo Zhang;Junbo Zhang;Tianrui Li;Hongmei Chen

  • A Rough-Set-Based Incremental Approach for Updating Approximations under Dynamic Maintenance Environments

    Hongmei Chen;Tianrui Li;Da Ruan;Jianhui Lin

  • Rough sets based matrix approaches with dynamic attribute variation in set-valued information systems

    Junbo Zhang;Tianrui Li;Da Ruan;Dun Liu

  • UniViLM: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation.

    Huaishao Luo;Lei Ji;Botian Shi;Haoyang Huang

Frequent Co-Authors

Dun Liu
Dun Liu Southwest Jiaotong University
Hamido Fujita
Hamido Fujita University of Technology Malaysia
Shi-Jinn Horng
Shi-Jinn Horng Asia University Taiwan
Da Ruan
Da Ruan Ghent University
Haiquan Zhao
Haiquan Zhao Southwest Jiaotong University
Bing Liu
Bing Liu University of Illinois at Chicago
Decui Liang
Decui Liang University of Electronic Science and Technology of China
Jie Lu
Jie Lu University of Technology Sydney
Guangquan Zhang
Guangquan Zhang University of Technology Sydney
Zheng Yan
Zheng Yan Xidian University

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