World's Best Scientists 2026 revealed!
Marina Vannucci

Marina Vannucci

D-Index & Metrics

Mathematics

D-Index
39
Citations
7181
World Ranking
2173
National Ranking
918

Computer Science

D-Index
41
Citations
7718
World Ranking
8793
National Ranking
3759

Marina Vannucci 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 Marina Vannucci 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: 142 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

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

Marina Vannucci 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 Marina Vannucci 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: 39 D-Index — 41st percentile

41% 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

  • 2012 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2006 - Fellow of the American Statistical Association (ASA)

Overview

Marina Vannucci is affiliated with Rice University in the United States and specializes primarily in the field of Computer Science. Their research covers a broad range of subfields, including Artificial Intelligence, Molecular Biology, Cognitive Neuroscience, Statistics and Probability, and Signal Processing.

The main topics of their work focus on Bayesian Methods and Mixture Models, Statistical Methods and Inference, Neural Dynamics and Brain Function, Gut Microbiota and Health, Metabolomics and Mass Spectrometry Studies, Statistical Methods and Bayesian Inference, and Functional Brain Connectivity Studies.

Marina Vannucci has published extensively, with notable recent papers including:

  • Bayesian statistics and modelling, 2021, Nature Reviews Methods Primers
  • Bayesian statistics and modelling, 2021, Nature Reviews Methods Primers
  • Bayesian graphical models for modern biological applications, 2021, Statistical Methods & Applications
  • Evidence of state-dependence in the effectiveness of responsive neurostimulation for seizure modulation, 2021, Brain Stimulation
  • Noradrenaline tracks emotional modulation of attention in human amygdala, 2023, Current Biology

Frequent co-authors they have collaborated with include Michele Guindani, Matthew D. Koslovsky, Beniamino Hadj-Amar, Meng Li, and Christine B. Peterson.

Their work has appeared in publication venues such as arXiv (Cornell University), Biometrics, The Annals of Applied Statistics, Bayesian Analysis, and Nature Reviews Methods Primers.

Marina Vannucci has received recognition in the form of fellowships. They were named a Fellow of the American Association for the Advancement of Science (AAAS) in 2012 and a Fellow of the American Statistical Association (ASA) in 2006.

Best Publications

  • Bayesian statistics and modelling

    Rens van de Schoot;Sarah Depaoli;Ruth King;Ruth King;Bianca Kramer

  • Multivariate Bayesian variable selection and prediction

    Philip J. Brown;Marina Vannucci;T. Fearn

  • Gene selection: a Bayesian variable selection approach

    Kyeong Eun Lee;Naijun Sha;Edward R. Dougherty;Marina Vannucci

  • Bayesian Variable Selection in Clustering High-Dimensional Data

    Mahlet G Tadesse;Naijun Sha;Marina Vannucci

  • A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data.

    Qianxing Mo;Ronglai Shen;Cui Guo;Marina Vannucci

  • Variable selection in clustering via Dirichlet process mixture models

    Sinae Kim;Mahlet G. Tadesse;Marina Vannucci

  • Bayesian Inference of Multiple Gaussian Graphical Models

    Christine B. Peterson;Francesco C. Stingo;Marina Vannucci

  • Bayesian wavelet regression on curves with application to a spectroscopic calibration problem

    Philip J. Brown;T. Fearn;Marina Vannucci

  • Bayes model averaging with selection of regressors

    Philip J. Brown;Marina Vannucci;T. Fearn

  • Incorporating biological information into linear models: A Bayesian approach to the selection of pathways and genes

    Francesco C. Stingo;Yian A. Chen;Mahlet G. Tadesse;Marina Vannucci

  • Bayesian variable selection in multinomial probit models to identify molecular signatures of disease stage.

    Naijun Sha;Marina Vannucci;Mahlet G. Tadesse;Philip J. Brown

  • Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis

    Jeffrey S Morris;Marina Vannucci;Philip J Brown;Raymond J Carroll

  • Detecting Traffic Anomalies through Aggregate Analysis of Packet Header Data

    Seong Soo Kim;A. L. Narasimha Reddy;Marina Vannucci

  • Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies

    Terrance Dean Savitsky;Marina Vannucci;Naijun Sha

  • Bayesian variable selection for the analysis of microarray data with censored outcomes

    Naijun Sha;Mahlet G. Tadesse;Marina Vannucci

  • Bayesian inference for gene expression and proteomics

    Kim-Anh Do;Peter Müller;Marina Vannucci

  • Covariance structure of wavelet coefficients: theory and models in a Bayesian perspective

    M. Vannucci;F. Corradi

  • Wavelet change-point prediction of transmembrane proteins.

    Pietro Lio;Marina Vannucci

  • Finding pathogenicity islands and gene transfer events in genome data.

    Pietro Liò;Marina Vannucci

  • The choice of variables in multivariate regression: a non-conjugate Bayesian decision theory approach

    Philip J. Brown;T. Fearn;Marina Vannucci

Frequent Co-Authors

Mingyu Liang
Mingyu Liang Medical College of Wisconsin
Allen W. Cowley
Allen W. Cowley Medical College of Wisconsin
Francesco Falciani
Francesco Falciani University of Liverpool
John M. Stern
John M. Stern University of California, Los Angeles
Raymond J. Carroll
Raymond J. Carroll Texas A&M University
Joanne R. Lupton
Joanne R. Lupton Texas A&M University
Kim Anh Do
Kim Anh Do The University of Texas MD Anderson Cancer Center
Robert S. Chapkin
Robert S. Chapkin Texas A&M University
Ching C. Lau
Ching C. Lau Baylor College of Medicine
Howard J. Jacob
Howard J. Jacob AbbVie (United States)

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