2026 Peter J. Bickel: Mathematics Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Mathematics	84	110	89	61	46	252	48701

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

4376
Citations
SIMULTANEOUS ANALYSIS OF LASSO AND DANTZIG SELECTOR

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

2906
Citations
Efficient and Adaptive Estimation for Semiparametric Models

Peter J. Bickel

2844
Citations
Some Asymptotic Theory for the Bootstrap

Peter J. Bickel;David A. Freedman

2370
Citations
Efficient and Adaptive Estimation for Semiparametric Models.

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

2338
Citations
Regularized estimation of large covariance matrices

Peter J. Bickel;Elizaveta Levina

1767
Citations
Covariance regularization by thresholding

Peter J. Bickel;Elizaveta Levina

1763
Citations
Mathematical Statistics: Basic Ideas and Selected Topics

Peter J. Bickel;Kjell A. Doksum

1503
Citations
On Some Global Measures of the Deviations of Density Function Estimates

P. J. Bickel;M. Rosenblatt

1058
Citations
Sparse permutation invariant covariance estimation

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

1030
Citations
Metalearners for estimating heterogeneous treatment effects using machine learning

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

952
Citations
Maximum Likelihood Estimation of Intrinsic Dimension

Elizaveta Levina;Peter J. Bickel

935
Citations
A nonparametric view of network models and Newman–Girvan and other modularities

Peter J. Bickel;Aiyou Chen

929
Citations
On Adaptive Estimation

P. J. Bickel

881
Citations
Obstacles to High-Dimensional Particle Filtering

Chris Snyder;Thomas Bengtsson;Peter Bickel;Jeff Anderson

881
Citations
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

753
Citations
The Earth Mover's distance is the Mallows distance: some insights from statistics

E. Levina;P. Bickel

745
Citations
Robust Estimates of Location: Survey and Advances.

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

736
Citations
An Analysis of Transformations Revisited

Peter J. Bickel;Kjell A. Doksum

708
Citations
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

570
Citations

Frequent Co-Authors

Ya'acov Ritov University of Michigan–Ann Arbor

Kjell A. Doksum University of Wisconsin–Madison

Elizaveta Levina University of Michigan–Ann Arbor

Susan E. Celniker Lawrence Berkeley National Laboratory

Anshul Kundaje Stanford University

Mark Gerstein Yale University

Mark D. Biggin Lawrence Berkeley National Laboratory

Joel Rozowsky Yale University

Thomas R. Gingeras Cold Spring Harbor Laboratory

Michael Snyder Stanford University

External Links

Wikipedia of Peter J. Bickel Personal website of Peter J. Bickel Google Scholar page

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