2026 Peter Bühlmann: Mathematics Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Mathematics	76	189	156	3	3	251	40281

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Mathematics

189

156

251

40281

Research.com Recognitions

2026 - Research.com Mathematics in Switzerland Leader Award
2025 - Research.com Mathematics in Switzerland Leader Award
2022 - Research.com Mathematics in Switzerland Leader Award
2016 - Fellow of the American Statistical Association (ASA)

Overview

Peter Bühlmann is affiliated with ETH Zurich in Switzerland. Their research spans across several key fields, primarily focused on Mathematics and Computer Science. Within these fields, their work extensively covers subfields such as Statistics and Probability, Artificial Intelligence, Molecular Biology, Control and Systems Engineering, and Epidemiology.

The main topics of their work include:

Statistical Methods and Inference
Statistical Methods and Bayesian Inference
Bayesian Modeling and Causal Inference
Advanced Causal Inference Techniques
Advanced Statistical Methods and Models
Bayesian Methods and Mixture Models
Machine Learning in Healthcare

They have contributed to the following recent papers:

Anchor Regression: Heterogeneous Data Meet Causality (2021), Journal of the Royal Statistical Society Series B (Statistical Methodology)
Predicting sepsis using deep learning across international sites: a retrospective development and validation study (2023), EClinicalMedicine
Seeded binary segmentation: a general methodology for fast and optimal changepoint detection (2022), Biometrika
Single-cell profiling of alveolar rhabdomyosarcoma reveals RAS pathway inhibitors as cell-fate hijackers with therapeutic relevance (2023), Science Advances
Multiomic profiling of the liver across diets and age in a diverse mouse population (2021), Cell Systems

The scientist frequently collaborates with several coauthors, including:

Nicolai Meinshausen
Domagoj Ćevid
Christoph Schultheiss
Solt Kovács
Corinne Emmenegger

They have published extensively in various venues, with the highest number of publications found in:

arXiv (Cornell University)
Statistical Science
Repository for Publications and Research Data (ETH Zurich)
bioRxiv (Cold Spring Harbor Laboratory)
Biometrika

In recognition of their contributions, the scientist was named Fellow of the American Statistical Association (ASA) in 2016.

Best Publications

MissForest—non-parametric missing value imputation for mixed-type data

Daniel J. Stekhoven;Peter L. Bühlmann

5754
Citations
High-dimensional graphs and variable selection with the Lasso

Nicolai Meinshausen;Peter Bühlmann

4599
Citations
The group lasso for logistic regression

Lukas Meier;Sara Van De Geer;Peter Bühlmann

2072
Citations
On asymptotically optimal confidence regions and tests for high-dimensional models

Sara van de Geer;Peter Bühlmann;Ya’acov Ritov;Ruben Dezeure

1650
Citations
BOOSTING ALGORITHMS: REGULARIZATION, PREDICTION AND MODEL FITTING

Peter Bühlmann;Torsten Hothorn

1317
Citations
A systematic comparison and evaluation of biclustering methods for gene expression data

Amela Prelić;Stefan Bleuler;Philip Zimmermann;Anja Wille

1220
Citations
Analyzing gene expression data in terms of gene sets

Jelle J. Goeman;Peter Bühlmann

1173
Citations
Boosting With the L2 Loss

Peter Lukas Bühlmann;Bin Yu

1160
Citations
Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm

Markus Kalisch;Peter Bühlmann

876
Citations
Analyzing Bagging

Unknown

828
Citations
On the conditions used to prove oracle results for the Lasso

Sara A. van de Geer;Peter Bühlmann

824
Citations
Causal inference by using invariant prediction: identification and confidence intervals

Jonas Peters;Peter Bühlmann;Nicolai Meinshausen

720
Citations
Causal Inference using Graphical Models with the R Package pcalg

Markus Kalisch;Martin Mächler;Diego Colombo;Marloes H. Maathuis

685
Citations
Sieve bootstrap for time series

Peter Bühlmann

590
Citations
Variable length Markov chains

Peter Bühlmann;Abraham J. Wyner

561
Citations
High-dimensional additive modeling

Lukas Meier;Sara van de Geer;Peter Bühlmann

549
Citations
Boosting for high-dimensional linear models

Peter Lukas Bühlmann

525
Citations
p-Values for High-Dimensional Regression

Nicolai Meinshausen;Lukas Meier;Peter Bühlmann

497
Citations
Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana

Anja Wille;Anja Wille;Philip Zimmermann;Philip Zimmermann;Eva Vranová;Eva Vranová;Andreas Fürholz;Andreas Fürholz

475
Citations
Bagging, Boosting and Ensemble Methods

Peter Bühlmann

401
Citations
Variable Length Markov Chains: Methodology, Computing and Software

Martin Mächler;Peter Bühlmann

96
Citations
Boosting with the L2-loss: regression and classification

Peter Lukas Bühlmann;Bin Yu

76
Citations

Frequent Co-Authors

Sara van de Geer ETH Zurich

Nicolai Meinshausen ETH Zurich

Wilhelm Gruissem ETH Zurich

Lars Hennig Swedish University of Agricultural Sciences

Bin Yu University of California, Berkeley

Bernhard Schölkopf Max Planck Institute for Intelligent Systems

Eckart Zitzler Lucerne University of Applied Sciences and Arts

Ruedi Aebersold ETH Zurich

Cun-Hui Zhang Rutgers, The State University of New Jersey

Lothar Thiele ETH Zurich

External Links

Wikipedia of Peter Bühlmann Personal website of Peter Bühlmann Google Scholar page

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