World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
43
Citations
6774
World Ranking
1711
National Ranking
737

Hulin Wu 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 Hulin Wu 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: 111 publications — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Hulin Wu 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 Hulin Wu 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: 43 D-Index — 54th percentile

54% 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

  • 2008 - Fellow of the American Statistical Association (ASA)

Overview

Hulin Wu is affiliated with The University of Texas Health Science Center at Houston in the United States. Their research primarily spans the fields of Medicine and Biochemistry, Genetics and Molecular Biology, with notable work in subfields such as Molecular Biology, Neurology, Epidemiology, Artificial Intelligence, and Pharmacology.

Their research focus includes several specific topics, among which are:

  • Bioinformatics and Genomic Networks
  • Musculoskeletal pain and rehabilitation
  • Traumatic Brain Injury and Neurovascular Disturbances
  • Gene expression and cancer classification
  • Biomedical Text Mining and Ontologies
  • Acute Ischemic Stroke Management
  • COVID-19 epidemiological studies

Hulin Wu has authored numerous scientific papers, with some recent publications including:

  • Controlling Multiple COVID-19 Epidemic Waves: An Insight from a Multi-scale Model Linking the Behaviour Change Dynamics to the Disease Transmission Dynamics (2022), Bulletin of Mathematical Biology
  • A content-based dataset recommendation system for researchers-a case study on Gene Expression Omnibus (GEO) repository (2020), Database
  • A content-based literature recommendation system for datasets to improve data reusability - A case study on Gene Expression Omnibus (GEO) datasets (2020), Journal of Biomedical Informatics
  • Scholarly recommendation systems: a literature survey (2023), Knowledge and Information Systems
  • Assessing Age-Specific Vaccination Strategies and Post-vaccination Reopening Policies for COVID-19 Control Using SEIR Modeling Approach (2022), Bulletin of Mathematical Biology

The scientist frequently collaborates with peers, including Vahed Maroufy, Ashraf Yaseen, Xinran Huang, Babak Soltanalizadeh, and Jennifer Kawi.

Key venues where Hulin Wu has published multiple works include:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Database
  • SSRN Electronic Journal
  • Research Square (Research Square)
  • Bulletin of Mathematical Biology

Hulin Wu was recognized as a Fellow of the American Statistical Association (ASA) in 2008.

Best Publications

  • On Identifiability of Nonlinear ODE Models and Applications in Viral Dynamics

    Hongyu Miao;Xiaohua Xia;Alan S. Perelson;Hulin Wu

  • Nonparametric Regression Methods for Longitudinal Data Analysis: Mixed-Effects Modeling Approaches

    Hulin Wu;Jin Ting Zhang

  • Population HIV-1 dynamics in vivo: applicable models and inferential tools for virological data from AIDS clinical trials.

    Hulin Wu;A. Adam Ding

  • Hierarchical Bayesian Methods for Estimation of Parameters in a Longitudinal HIV Dynamic System

    Yangxin Huang;Dacheng Liu;Hulin Wu

  • Parameter Estimation for Differential Equation Models Using a Framework of Measurement Error in Regression Models

    Hua Liang;Hulin Wu

  • Local Polynomial Mixed-Effects Models for Longitudinal Data

    Hulin Wu;Jin-Ting Zhang

  • Parameter Identifiability and Estimation of HIV/AIDS Dynamic Models

    Hulin Wu;Haihong Zhu;Hongyu Miao;Alan S. Perelson

  • Nonparametric regression methods for longitudinal data analysis

    Hulin Wu;Jin-Ting Zhang

  • Modelling the distribution of plant species using the autologistic regression model

    Hulin Wu;F Red W. Huffer

  • Markov chain Monte Carlo for autologistic regression models with application to the distribution of plant species

    Fred W. Huffer;Hulin Wu

  • A note on conditional AIC for linear mixed-effects models

    Hua Liang;Hulin Wu;Guohua Zou

  • Modeling HIV dynamics and antiviral response with consideration of time-varying drug exposures, adherence and phenotypic sensitivity

    Yangxin Huang;Susan L. Rosenkranz;Hulin Wu

  • Estimation of HIV dynamic parameters

    Hulin Wu;Hulin Wu;A. Adam Ding;Victor De Gruttola

  • The relationship between virologic and immunologic responses in AIDS clinical research using mixed-effects varying-coefficient models with measurement error.

    Hua Liang;Hulin Wu;Raymond J. Carroll

  • Stochastic modeling of the dynamics of CD4+ T-cell infection by HIV and some Monte Carlo studies

    Wai Yuan Tan;Hulin Wu

  • Sieve Estimation of Constant and Time-Varying Coefficients in Nonlinear Ordinary Differential Equation Models by Considering Both Numerical Error and Measurement Error.

    Hongqi Xue;Hongyu Miao;Hulin Wu

  • Relationships between antiviral treatment effects and biphasic viral decay rates in modeling HIV dynamics

    A.Adam Ding;Hulin Wu

  • Statistical methods for HIV dynamic studies in AIDS clinical trials.

    Hulin Wu

  • Modeling long-term HIV dynamics and antiretroviral response: effects of drug potency, pharmacokinetics, adherence, and drug resistance.

    Hulin Wu;Yangxin Huang;Edward P Acosta;Susan L Rosenkranz

  • Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling

    Hulin Wu;Tao Lu;Hongqi Xue;Hua Liang

Frequent Co-Authors

Hua Liang
Hua Liang George Washington University
David J. Topham
David J. Topham University of Rochester Medical Center
Alan S. Perelson
Alan S. Perelson Los Alamos National Laboratory
Tim R. Mosmann
Tim R. Mosmann University of Rochester Medical Center
Xia Jin
Xia Jin Chinese Academy of Sciences
Daniel R. Kuritzkes
Daniel R. Kuritzkes Brigham and Women's Hospital
Edward P. Acosta
Edward P. Acosta University of Alabama at Birmingham
Michael M. Lederman
Michael M. Lederman Case Western Reserve University
John J. Treanor
John J. Treanor University of Rochester Medical Center
Alan L. Landay
Alan L. Landay The University of Texas Medical Branch at Galveston

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Mathematics in the USA opens up a wide range of career opportunities, many of which benefit from complementary qualifications. For those considering advancing their careers, exploring mba programs that accept transfer credits can be an excellent way to leverage existing coursework and accelerate degree completion.

Fields like data science and analytics heavily rely on mathematical skills. Pursuing a data analytics masters programs can provide specialized knowledge that enhances employability in tech, finance, and business sectors.

For professionals interested in leadership roles but concerned about entry requirements, identifying what mba programs can i get into helps narrow down options based on accessibility and acceptance rates. Many students find that enrolling in the easiest mba programs online offers a practical balance of quality education and manageable admissions standards.

Overall, combining a mathematics background with strategic online degrees can significantly expand career pathways, making it easier to progress into management or specialized data roles.

Best Scientists Citing Hulin Wu

Trending Scientists

Recently Published Articles