World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
8573
World Ranking
9170
National Ranking
3902

Lin Tan 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 Lin Tan 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: 67 publications — 1st percentile

1% of scientists in this discipline score the same or lower.

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

Lin Tan 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 Lin Tan 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Lin Tan is affiliated with Purdue University West Lafayette in the United States and has contributed extensively to research in the fields of Medicine and Biochemistry, Genetics and Molecular Biology. Their work spans multiple subfields including Molecular Biology, Epidemiology, Cancer Research, Hematology, and Infectious Diseases.

Their recent published papers cover a range of topics, highlighting research on COVID-19, leukemia, lipid metabolism, cardiac protection mechanisms, and graft-versus-host disease. Significant publications include:

  • Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score, 2020, Clinical Infectious Diseases
  • Targeting MCL-1 Dysregulates Cell Metabolism and Leukemia-Stroma Interactions and Re-sensitizes Acute Myeloid Leukemia to BCL-2 Inhibition, 2020, Haematologica
  • Choline Kinase Alpha 2 Acts as a Protein Kinase to Promote Lipolysis of Lipid Droplets, 2021, Molecular Cell
  • ATF4 Protects the Heart From Failure by Antagonizing Oxidative Stress, 2022, Circulation Research
  • Mucus-degrading Bacteroides Link Carbapenems to Aggravated Graft-Versus-Host Disease, 2022, Cell

The topics covered in Lin Tan's research predominantly focus on:

  • Liver Disease Diagnosis and Treatment
  • Hepatitis B Virus Studies
  • Hepatitis C Virus Research
  • Mitochondrial Function and Pathology
  • Cancer, Hypoxia, and Metabolism
  • COVID-19 Clinical Research Studies
  • Acute Myeloid Leukemia Research

Lin Tan has collaborated frequently with several researchers including Philip L. Lorenzi, Yongping Yang, Huabao Liu, Qinghua Shang, and Yong-Ping Chen.

Their research has been published repeatedly in notable venues such as:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Blood
  • Nature Communications
  • SSRN Electronic Journal
  • Journal of Hepatology

Best Publications

  • Automatically learning semantic features for defect prediction

    Song Wang;Taiyue Liu;Lin Tan

  • Heterogeneous Defect Prediction

    Jaechang Nam;Wei Fu;Sunghun Kim;Tim Menzies

  • Hibernator: helping disk arrays sleep through the winter

    Qingbo Zhu;Zhifeng Chen;Lin Tan;Yuanyuan Zhou

  • A High Throughput String Matching Architecture for Intrusion Detection and Prevention

    Lin Tan;Timothy Sherwood

  • CURE: Code-Aware Neural Machine Translation for Automatic Program Repair

    Nan Jiang;Thibaud Lutellier;Lin Tan

  • Have things changed now?: an empirical study of bug characteristics in modern open source software

    Zhenmin Li;Lin Tan;Xuanhui Wang;Shan Lu

  • SherLog: error diagnosis by connecting clues from run-time logs

    Ding Yuan;Haohui Mai;Weiwei Xiong;Lin Tan

  • CoCoNuT: combining context-aware neural translation models using ensemble for program repair

    Thibaud Lutellier;Hung Viet Pham;Lawrence Pang;Yitong Li

  • Personalized defect prediction

    Tian Jiang;Lin Tan;Sunghun Kim

  • AsDroid: detecting stealthy behaviors in Android applications by user interface and program behavior contradiction

    Jianjun Huang;Xiangyu Zhang;Lin Tan;Peng Wang

  • Deep Semantic Feature Learning for Software Defect Prediction

    Song Wang;Taiyue Liu;Jaechang Nam;Lin Tan

  • /*icomment: bugs or bad comments?*/

    Lin Tan;Ding Yuan;Gopal Krishna;Yuanyuan Zhou

  • AutoComment: mining question and answer sites for automatic comment generation

    Edmund Wong;Jinqiu Yang;Lin Tan

  • Bug characteristics in open source software

    Lin Tan;Chen Liu;Zhenmin Li;Xuanhui Wang

  • @tComment: Testing Javadoc Comments to Detect Comment-Code Inconsistencies

    Shin Hwei Tan;Darko Marinov;Lin Tan;Gary T. Leavens

  • Online defect prediction for imbalanced data

    Ming Tan;Lin Tan;Sashank Dara;Caleb Mayeux

  • CRADLE: Cr oss-backend v a lidation to D etect and L ocalize bugs in D e ep learning libraries

    Hung Viet Pham;Thibaud Lutellier;Weizhen Qi;Lin Tan

  • CloCom: Mining existing source code for automatic comment generation

    Edmund Wong;Taiyue Liu;Lin Tan

  • Do time of day and developer experience affect commit bugginess

    Jon Eyolfson;Lin Tan;Patrick Lam

  • Discovering, reporting, and fixing performance bugs

    Adrian Nistor;Tian Jiang;Lin Tan

Frequent Co-Authors

Yuanyuan Zhou
Yuanyuan Zhou University of California, San Diego
Xiangyu Zhang
Xiangyu Zhang Purdue University West Lafayette
Timothy Sherwood
Timothy Sherwood University of California, Santa Barbara
Darko Marinov
Darko Marinov University of Illinois at Urbana-Champaign
Gary T. Leavens
Gary T. Leavens University of Central Florida
ChengXiang Zhai
ChengXiang Zhai University of Illinois at Urbana-Champaign
Abram Hindle
Abram Hindle University of Alberta
Xuanhui Wang
Xuanhui Wang Google (United States)
Nenad Medvidovic
Nenad Medvidovic University of Southern California
Sunghun Kim
Sunghun Kim Hong Kong University of Science and Technology

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