World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
43
Citations
11676
World Ranking
1658
National Ranking
716

Ryan J. Tibshirani 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 Ryan J. Tibshirani 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: 105 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Ryan J. Tibshirani 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 Ryan J. Tibshirani 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.

Overview

Ryan J. Tibshirani is affiliated with the University of California, Berkeley in the United States. Their research spans multiple disciplines including mathematics, computer science, and medicine, with a substantial focus on statistics and probability, artificial intelligence, and epidemiology.

Their primary research topics include data-driven disease surveillance, COVID-19 epidemiological studies, statistical methods and inference, advanced statistical methods and models, influenza virus research studies, machine learning and data classification, and anomaly detection techniques and applications.

Frequent collaborators in their research include Alden Green, Roni Rosenfeld, Addison J. Hu, Daniel J. McDonald, and Natalia L. Oliveira. These partnerships have contributed to a growing body of work published in a variety of venues.

Ryan J. Tibshirani frequently publishes in the following venues:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • The Annals of Statistics
  • Proceedings of the National Academy of Sciences
  • Statistical Science

Selected recent publications include:

  • Surprises in high-dimensional ridgeless least squares interpolation, 2022, The Annals of Statistics
  • Best Subset, Forward Stepwise or Lasso? Analysis and Recommendations Based on Extensive Comparisons, 2020, Statistical Science
  • The US COVID-19 Trends and Impact Survey: Continuous real-time measurement of COVID-19 symptoms, risks, protective behaviors, testing, and vaccination, 2021, Proceedings of the National Academy of Sciences
  • Conformal prediction beyond exchangeability, 2023, The Annals of Statistics
  • Collaborative Hubs: Making the Most of Predictive Epidemic Modeling, 2022, American Journal of Public Health

Best Publications

  • The solution path of the generalized lasso

    Ryan J. Tibshirani;Jonathan Taylor

  • A SIGNIFICANCE TEST FOR THE LASSO.

    Richard Lockhart;Jonathan Taylor;Ryan J. Tibshirani;Robert Tibshirani

  • Strong rules for discarding predictors in lasso-type problems

    Robert Tibshirani;Jacob Bien;Jerome Friedman;Trevor Hastie

  • Distribution-Free Predictive Inference for Regression

    Jing Lei;Max G'Sell;Alessandro Rinaldo;Ryan J. Tibshirani

  • The Lasso Problem and Uniqueness

    Ryan J. Tibshirani

  • Surprises in High-Dimensional Ridgeless Least Squares Interpolation.

    Trevor Hastie;Andrea Montanari;Saharon Rosset;Ryan J. Tibshirani

  • Adaptive piecewise polynomial estimation via trend filtering

    Ryan J. Tibshirani

  • Degrees of freedom in lasso problems

    Ryan J. Tibshirani;Jonathan Taylor

  • Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

    Unknown

  • Exact Post-Selection Inference for Sequential Regression Procedures

    Ryan J. Tibshirani;Jonathan Taylor;Richard Lockhart;Robert Tibshirani

  • Best Subset, Forward Stepwise or Lasso? Analysis and Recommendations Based on Extensive Comparisons

    Unknown

  • Trend filtering on graphs

    Yu-Xiang Wang;James Sharpnack;Alexander J. Smola;Ryan J. Tibshirani

  • The US COVID-19 Trends and Impact Survey: Continuous real-time measurement of COVID-19 symptoms, risks, protective behaviors, testing, and vaccination

    Unknown

  • An open challenge to advance probabilistic forecasting for dengue epidemics.

    Michael A. Johansson;Michael A. Johansson;Karyn M. Apfeldorf;Scott Dobson;Jason Devita

  • Predictive inference with the jackknife

    Rina Foygel Barber;Emmanuel J. Candès;Aaditya Ramdas;Ryan J. Tibshirani

  • Conformal prediction beyond exchangeability

    Unknown

  • Extended Comparisons of Best Subset Selection, Forward Stepwise Selection, and the Lasso

    Trevor Hastie;Robert Tibshirani;Ryan J. Tibshirani

  • The United States COVID-19 Forecast Hub dataset

    Unknown

  • Nearly-Isotonic Regression

    Ryan J. Tibshirani;Holger Hoefling;Robert Tibshirani

  • Flexible Modeling of Epidemics with an Empirical Bayes Framework

    Logan C. Brooks;David C. Farrow;Sangwon Hyun;Ryan J. Tibshirani

  • Collaborative efforts to forecast seasonal influenza in the United States, 2015–2016

    Craig J. McGowan;Matthew Biggerstaff;Michael Johansson;Karyn M. Apfeldorf

  • A bias correction for the minimum error rate in cross-validation

    Ryan J. Tibshirani;Robert Tibshirani

  • The limits of distribution-free conditional predictive inference

    Rina Foygel Barber;Emmanuel J Candès;Aaditya Ramdas;Ryan J Tibshirani

  • Efficient Implementations of the Generalized Lasso Dual Path Algorithm

    Taylor B. Arnold;Ryan J. Tibshirani

  • Conformal Prediction Under Covariate Shift

    Ryan J. Tibshirani;Rina Foygel Barber;Emmanuel J. Candès;Aaditya Ramdas

Frequent Co-Authors

Robert Tibshirani
Robert Tibshirani Stanford University
Jonathan Taylor
Jonathan Taylor Stanford University
Roni Rosenfeld
Roni Rosenfeld Carnegie Mellon University
Larry Wasserman
Larry Wasserman Carnegie Mellon University
Alessandro Rinaldo
Alessandro Rinaldo The University of Texas at Austin
Emmanuel J. Candès
Emmanuel J. Candès Stanford University
Alexander J. Smola
Alexander J. Smola Amazon (United States)
Saharon Rosset
Saharon Rosset Tel Aviv University
Trevor Hastie
Trevor Hastie Stanford University
J. Zico Kolter
J. Zico Kolter Carnegie Mellon University

External Links

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