World's Best Scientists 2026 revealed!
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Computer Science
Taiwan
2025

D-Index & Metrics

Computer Science

D-Index
66
Citations
108954
World Ranking
2245
National Ranking
13

Chih-Jen Lin 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 Chih-Jen Lin 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: 158 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Chih-Jen Lin 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 Chih-Jen Lin 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: 66 D-Index — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Taiwan Leader Award
  • 2022 - Research.com Computer Science in Taiwan Leader Award

Overview

Chih-Jen Lin is affiliated with National Taiwan University in Taiwan. Their research primarily spans the fields of Computer Science and Engineering, with a strong emphasis on Artificial Intelligence and related subfields such as Computational Mechanics, Computer Vision and Pattern Recognition, Civil and Structural Engineering, and Numerical Analysis.

Their recent publications include:

  • "Parameter Selection for Linear Support Vector Regression," 2020, IEEE Transactions on Neural Networks and Learning Systems
  • "One-Class SVM Probabilistic Outputs," 2024, IEEE Transactions on Neural Networks and Learning Systems
  • "A Study on Truncated Newton Methods for Linear Classification," 2021, IEEE Transactions on Neural Networks and Learning Systems
  • "Practical Counterfactual Policy Learning for Top-K Recommendations," 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • "Newton Methods for Convolutional Neural Networks," 2020, ACM Transactions on Intelligent Systems and Technology

Frequent publication venues for Chih-Jen Lin include:

  • arXiv (Cornell University)
  • IEEE Transactions on Neural Networks and Learning Systems
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • ACM Transactions on Intelligent Systems and Technology
  • Proceedings of the AAAI Conference on Artificial Intelligence

The scientist often collaborates with other researchers in their field, with frequent coauthors being Jie-Jyun Liu, Pin-Yen Lin, Jui-Nan Yen, Li-Chung Lin, and Cheng-Hung Liu.

The main topics covered in their work include:

  • Sparse and Compressive Sensing Techniques
  • Text and Document Classification Technologies
  • Stochastic Gradient Optimization Techniques
  • Anomaly Detection Techniques and Applications
  • Water Systems and Optimization
  • Machine Learning and ELM
  • Face and Expression Recognition

Best Publications

  • LIBSVM: A library for support vector machines

    Chih-Chung Chang;Chih-Jen Lin

  • A comparison of methods for multiclass support vector machines

    Chih-Wei Hsu;Chih-Jen Lin

  • LIBLINEAR: A Library for Large Linear Classification

    Rong-En Fan;Kai-Wei Chang;Cho-Jui Hsieh;Xiang-Rui Wang

  • A Practical Guide to Support Vector Classication

    Chih-Wei Hsu;Chih-Chung Chang;Chih-Jen Lin

  • Probability Estimates for Multi-class Classification by Pairwise Coupling

    Ting-Fan Wu;Chih-Jen Lin;Ruby C. Weng

  • Asymptotic behaviors of support vector machines with Gaussian kernel

    S. Sathiya Keerthi;Chih-Jen Lin

  • Working Set Selection Using Second Order Information for Training Support Vector Machines

    Rong-En Fan;Pai-Hsuen Chen;Chih-Jen Lin

  • Projected Gradient Methods for Nonnegative Matrix Factorization

    Chih-Jen Lin

  • Combining SVMs with Various Feature Selection Strategies

    Yi-Wei Chen;Chih-Jen Lin

  • Load forecasting using support vector Machines: a study on EUNITE competition 2001

    Bo-Juen Chen;Ming-Wei Chang;Chih-Jen lin

  • A dual coordinate descent method for large-scale linear SVM

    Cho-Jui Hsieh;Kai-Wei Chang;Chih-Jen Lin;S. Sathiya Keerthi

  • Predicting subcellular localization of proteins for Gram-negative bacteria by support vector machines based on n-peptide compositions

    Chin-Sheng Yu;Chih-Jen Lin;Jenn-Kang Hwang

  • A note on Platt's probabilistic outputs for support vector machines

    Hsuan-Tien Lin;Chih-Jen Lin;Ruby C. Weng

  • Parallel Spectral Clustering in Distributed Systems

    Wen-Yen Chen;Yangqiu Song;Hongjie Bai;Chih-Jen Lin

  • Field-aware Factorization Machines for CTR Prediction

    Yuchin Juan;Yong Zhuang;Wei-Sheng Chin;Chih-Jen Lin

  • Training ν -Support Vector Classifiers: Theory and Algorithms

    Chih-Chung Chang;Chih-Jen Lin

  • Training and Testing Low-degree Polynomial Data Mappings via Linear SVM

    Yin-Wen Chang;Cho-Jui Hsieh;Kai-Wei Chang;Michael Ringgaard

  • A Comparison of Methods for Multi-class Support Vector Machines

    Chih-Wei Hsu;Chih-Jen Lin

  • A tutorial on ν‐support vector machines

    Pai-Hsuen Chen;Chih-Jen Lin;Bernhard Schölkopf

  • On the Convergence of Multiplicative Update Algorithms for Nonnegative Matrix Factorization

    Chih-Jen Lin

Frequent Co-Authors

Cho-Jui Hsieh
Cho-Jui Hsieh University of California, Los Angeles
Kai-Wei Chang
Kai-Wei Chang University of California, Los Angeles
Shu-Cherng Fang
Shu-Cherng Fang North Carolina State University
Miguel Ramalho-Santos
Miguel Ramalho-Santos University of Toronto
Ming-Wei Chang
Ming-Wei Chang Google (United States)
Yangqiu Song
Yangqiu Song Hong Kong University of Science and Technology
Xiangzhong Yang
Xiangzhong Yang University of Connecticut
Richard A. Anderson
Richard A. Anderson University of Edinburgh
Jorge J. Moré
Jorge J. Moré Argonne National Laboratory
Chee Wee Liu
Chee Wee Liu National Taiwan University

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