World's Best Scientists 2026 revealed!
Award Badge
Mathematics
USA
2026

D-Index & Metrics

Mathematics

D-Index
84
Citations
48701
World Ranking
110
National Ranking
61

Peter J. Bickel 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 Peter J. Bickel 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: 82 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: 252 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Peter J. Bickel 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 Peter J. Bickel 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: 137 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: 84 D-Index — 97th percentile

97% 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
  • 2018 - Samuel S. Wilks Memorial Award, American Statistical Association (ASA)
  • 2009 - SIAM Fellow For contributions to mathematical statistics.
  • 1986 - Member of the National Academy of Sciences
  • 1986 - Fellow of the American Academy of Arts and Sciences
  • 1981 - COPSS Presidents' Award
  • 1981 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 1980 - Wald Memorial Lecturer
  • 1973 - Fellow of the American Statistical Association (ASA)
  • 1970 - Fellow of John Simon Guggenheim Memorial Foundation

Overview

Peter J. Bickel is affiliated with the University of California, Berkeley in the United States. Their research encompasses various domains within mathematics, with a particular focus on statistics and probability.

Their recent publications include the following papers:

  • Hierarchical Community Detection by Recursive Partitioning, 2020, Journal of the American Statistical Association
  • SOME PROBLEMS ON THE ESTIMATION OF UNIMODAL DENSITIES, 2021, UNC Libraries
  • Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network, 2021, Nature Communications
  • Interpretable sensitivity analysis for balancing weights, 2023, Journal of the Royal Statistical Society Series A (Statistics in Society)
  • Correlations with tailored extremal properties, 2020, arXiv (Cornell University)

Frequent co-authors collaborating with Peter J. Bickel include:

  • Purnamrita Sarkar
  • Peter Arner
  • Aiyou Chen
  • Susan Athey
  • Guido W. Imbens

Key publication venues for their work are:

  • arXiv (Cornell University)
  • Journal of the American Statistical Association
  • Nature Communications
  • Journal of the Royal Statistical Society Series A (Statistics in Society)
  • UNC Libraries

Their main fields of study are:

  • Mathematics

Subfields of study include:

  • Statistics and Probability
  • Molecular Biology
  • Artificial Intelligence
  • Statistical and Nonlinear Physics
  • Signal Processing

Peter J. Bickel's main topics of work cover:

  • Statistical Methods and Inference
  • Complex Network Analysis Techniques
  • Advanced Causal Inference Techniques
  • Advanced Statistical Methods and Models
  • Bioinformatics and Genomic Networks
  • Statistical Methods and Bayesian Inference
  • Bayesian Methods and Mixture Models

Throughout their career, Peter J. Bickel has been recognized with several awards, including:

  • Samuel S. Wilks Memorial Award, American Statistical Association (2018)
  • SIAM Fellow (2009), for contributions to mathematical statistics
  • Member of the National Academy of Sciences (1986)
  • Fellow of the American Academy of Arts and Sciences (1986)
  • Fellow of the American Association for the Advancement of Science (AAAS) (1981)
  • COPSS Presidents' Award (1981)
  • Wald Memorial Lecturer (1980)
  • Fellow of the American Statistical Association (ASA) (1973)
  • Fellow of John Simon Guggenheim Memorial Foundation (1970)

Best Publications

  • Mathematical Statistics : Basic Ideas and Selected Topics, Volumes I-II Package

    Peter .J. Bickel;Kjell A. Doksum

  • SIMULTANEOUS ANALYSIS OF LASSO AND DANTZIG SELECTOR

    Peter J. Bickel;Ya' Acov Ritov;Alexandre B. Tsybakov

  • Efficient and Adaptive Estimation for Semiparametric Models

    Peter J. Bickel

  • Some Asymptotic Theory for the Bootstrap

    Peter J. Bickel;David A. Freedman

  • Efficient and Adaptive Estimation for Semiparametric Models.

    K. A. Do;P. J. Bickel;C. A. J. Klaassen;Y. Ritov

  • Regularized estimation of large covariance matrices

    Peter J. Bickel;Elizaveta Levina

  • Covariance regularization by thresholding

    Peter J. Bickel;Elizaveta Levina

  • Mathematical Statistics: Basic Ideas and Selected Topics

    Peter J. Bickel;Kjell A. Doksum

  • On Some Global Measures of the Deviations of Density Function Estimates

    P. J. Bickel;M. Rosenblatt

  • Sparse permutation invariant covariance estimation

    Adam J. Rothman;Peter J. Bickel;Elizaveta Levina;Ji Zhu

  • Metalearners for estimating heterogeneous treatment effects using machine learning

    Sören R. Künzel;Jasjeet S. Sekhon;Peter J. Bickel;Bin Yu

  • Maximum Likelihood Estimation of Intrinsic Dimension

    Elizaveta Levina;Peter J. Bickel

  • A nonparametric view of network models and Newman–Girvan and other modularities

    Peter J. Bickel;Aiyou Chen

  • On Adaptive Estimation

    P. J. Bickel

  • Obstacles to High-Dimensional Particle Filtering

    Chris Snyder;Thomas Bengtsson;Peter Bickel;Jeff Anderson

  • Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations

    Peter J. Bickel;Elizaveta Levina

  • The Earth Mover's distance is the Mallows distance: some insights from statistics

    E. Levina;P. Bickel

  • Robust Estimates of Location: Survey and Advances.

    P. Prescott;D. R. Andrews;P. J. Bickel;F. R. Hampei

  • An Analysis of Transformations Revisited

    Peter J. Bickel;Kjell A. Doksum

  • RESAMPLING FEWER THAN n OBSERVATIONS: GAINS, LOSSES, AND REMEDIES FOR LOSSES

    P. J. Bickel;P. J. Bickel;F. Götze;F. Götze;W. R. van Zwet;W. R. van Zwet

Frequent Co-Authors

Ya'acov Ritov
Ya'acov Ritov University of Michigan–Ann Arbor
Kjell A. Doksum
Kjell A. Doksum University of Wisconsin–Madison
Elizaveta Levina
Elizaveta Levina University of Michigan–Ann Arbor
Susan E. Celniker
Susan E. Celniker Lawrence Berkeley National Laboratory
Anshul Kundaje
Anshul Kundaje Stanford University
Mark Gerstein
Mark Gerstein Yale University
Mark D. Biggin
Mark D. Biggin Lawrence Berkeley National Laboratory
Joel Rozowsky
Joel Rozowsky Yale University
Thomas R. Gingeras
Thomas R. Gingeras Cold Spring Harbor Laboratory
Michael Snyder
Michael Snyder Stanford University

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

For students exploring Mathematics in the USA, branching into related fields can enhance career opportunities and skill sets. Many graduates find that pursuing a masters in data analytics complements their math background, equipping them with practical tools to analyze big data across industries.

For those interested in leadership roles, an MBA can be a valuable addition. If access and flexibility are major concerns, considering one of the easiest MBA program to get into or exploring the easiest online MBA programs may provide a manageable pathway toward acquiring business skills alongside a technical foundation.

For professionals aiming to excel in business administration at an advanced level without committing to lengthy study periods, the best 1 year DBA program online offers a practical, time-efficient option to combine expertise in mathematics and administration.

Exploring these related degrees can help students integrate mathematical thinking with data-driven decision-making and business acumen, opening doors to careers in analytics, finance, management, and beyond.

Best Scientists Citing Peter J. Bickel

Trending Scientists

Recently Published Articles