World's Best Scientists 2026 revealed!
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Mathematics
USA
2026

D-Index & Metrics

Mathematics

D-Index
80
Citations
30762
World Ranking
145
National Ranking
84

Danyu Lin publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Danyu Lin sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 198 publications — 61st percentile

61% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Danyu Lin D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Danyu Lin sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 80 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Mathematics in United States Leader Award
  • 2025 - Research.com Mathematics in United States Leader Award
  • 2000 - Fellow of the American Statistical Association (ASA)

Overview

Danyu Lin is affiliated with the University of North Carolina at Chapel Hill in the United States. Their research primarily focuses on fields including Biochemistry, Genetics, and Molecular Biology. Within these broad areas, Lin's work extensively covers Genetics, Statistics and Probability, Molecular Biology, Infectious Diseases, and Artificial Intelligence.

The scientist's main research topics include:

  • Genetic Associations and Epidemiology
  • Statistical Methods and Inference
  • SARS-CoV-2 and COVID-19 Research
  • Genetic and phenotypic traits in livestock
  • Genetic Mapping and Diversity in Plants and Animals
  • Single-cell and spatial transcriptomics
  • Statistical Methods in Clinical Trials

Lin has collaborated frequently with several co-authors, among them:

  • Donglin Zeng
  • Kari E. North
  • Christy L. Avery
  • Heather M. Highland
  • Yangjianchen Xu

Their work has been published predominantly in the following venues:

  • UNC Libraries
  • bioRxiv (Cold Spring Harbor Laboratory)
  • New England Journal of Medicine
  • BMC Genomics
  • Genetic Epidemiology

Selected recent papers authored or co-authored by Danyu Lin include:

  • "Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data," 2022, Nature Genetics
  • "Effectiveness of Bivalent Boosters against Severe Omicron Infection," 2023, New England Journal of Medicine
  • "Marginal regression models for recurrent and terminal events," 2021, UNC Libraries
  • "Association of Primary and Booster Vaccination and Prior Infection With SARS-CoV-2 Infection and Severe COVID-19 Outcomes," 2022, JAMA
  • "Durability of Bivalent Boosters against Omicron Subvariants," 2023, New England Journal of Medicine

In 2000, Lin was recognized as a Fellow of the American Statistical Association (ASA).

Best Publications

  • The Robust Inference for the Cox Proportional Hazards Model

    D. Y. Lin;L. J. Wei

  • Regression analysis of multivariate incomplete failure time data by modeling marginal distributions

    L. J. Wei;D. Y. Lin;L. Weissfeld

  • Checking the Cox model with cumulative sums of martingale-based residuals

    D. Y. Lin;L. J. Wei;Z. Ying

  • TIME-DEPENDENT COVARIATES IN THE COX PROPORTIONAL-HAZARDS REGRESSION MODEL

    Lloyd D. Fisher;Danyu Lin

  • Semiparametric regression for the mean and rate functions of recurrent events

    D. Y. Lin;L. J. Wei;I. Yang;Z. Ying

  • METHODS FOR ANALYZING HEALTH CARE UTILIZATION AND COSTS

    P. Diehr;D. Yanez;Arlene S. Ash;M. Hornbrook

  • Semiparametric analysis of the additive risk model

    D. Y. Lin;Zhiliang Ying

  • Assessing the Sensitivity of Regression Results to Unmeasured Confounders in Observational Studies

    D. Y. Lin;B. M. Psaty;R. A. Kronmal

  • Cox regression analysis of multivariate failure time data: The marginal approach

    D. Y. Lin

  • Estimating the proportion of treatment effect explained by a surrogate marker

    Danyu Lin;T. R. Fleming;V. De Gruttola

  • Estimating medical costs from incomplete follow-up data.

    Danyu Lin;E. J. Feuer;R. Etzioni;Y. Wax

  • NON-PARAMETRIC INFERENCE FOR CUMULATIVE INCIDENCE FUNCTIONS IN COMPETING RISKS STUDIES

    D. Y. Lin

  • Rank-based inference for the accelerated failure time model

    Zhezhen Jin;D. Y. Lin;L. J. Wei;Zhiliang Ying

  • Assessment and control for confounding by indication in observational studies.

    Bruce M. Psaty;Thomas D. Koepsell;Danyu Lin;Noel S. Weiss

  • Maximum likelihood estimation in semiparametric regression models with censored data

    Donglin Zeng;Danyu Lin

  • A randomized, double-blind, placebo-controlled trial of ursodeoxycholic acid in primary biliary cirrhosis

    Burton Combes;Robert L. Carithers;Willis C. Maddrey;Willis C. Maddrey;Danyu Lin

  • Semiparametric and Nonparametric Regression Analysis of Longitudinal Data

    D. Y Lin;Z Ying

  • Cox Regression with Incomplete Covariate Measurements

    Danyu Lin;Z. Ying

  • Nonparametric analysis of recurrent events and death.

    Debashis Ghosh;D. Y. Lin

  • Model‐Checking Techniques Based on Cumulative Residuals

    D. Y. Lin;L. J. Wei;Z. Ying

  • Linear regression analysis of censored survival data based on rank tests

    L. J. Wei;Z. Ying;Danyu Lin

Frequent Co-Authors

Bruce M. Psaty
Bruce M. Psaty University of Washington
Kari E. North
Kari E. North University of North Carolina at Chapel Hill
Zhiliang Ying
Zhiliang Ying Columbia University
Stephan Ripke
Stephan Ripke Massachusetts General Hospital
Patrick F. Sullivan
Patrick F. Sullivan University of North Carolina at Chapel Hill
Eric Boerwinkle
Eric Boerwinkle The University of Texas Health Science Center at Houston
Danielle Posthuma
Danielle Posthuma Vrije Universiteit Amsterdam
Gerardo Heiss
Gerardo Heiss University of North Carolina at Chapel Hill
Charles Kooperberg
Charles Kooperberg Fred Hutchinson Cancer Research Center
Shaun Purcell
Shaun Purcell Harvard Medical School

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