2026 Bernhard Schölkopf: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Best Scientists	182	560	515	21	21	1289	233981
Computer Science	180	11	11	2	2	1233	213304

Bernhard Schölkopf publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Bernhard Schölkopf sits on this spectrum.

32 publications 991+

This scientist: 1,233 publications — 100th percentile

100% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Bernhard Schölkopf D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Bernhard Schölkopf sits on this spectrum.

30 D-Index 131+

This scientist: 180 D-Index — 100th percentile

100% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

2026 - Research.com Computer Science in Germany Leader Award
2025 - Research.com Best Scientists Award
2025 - Research.com Computer Science in Germany Leader Award
2023 - Research.com Computer Science in Germany Leader Award
2022 - Research.com Computer Science in Germany Leader Award
2019 - BBVA Foundation Frontiers of Knowledge Award
2017 - ACM Fellow For contributions to the theory and practice of machine learning
2016 - German National Academy of Sciences Leopoldina - Deutsche Akademie der Naturforscher Leopoldina – Nationale Akademie der Wissenschaften Informatics
2011 - Max Planck Research Award Intelligent systems
2006 - IAPR J. K. Aggarwal Prize "For advancing the field of kernel methods and showing its wide applicability to pattern recognition problems."
Member of the European Academy of Sciences and Arts
Member of the European Academy of Sciences and Arts
Member of the European Academy of Sciences and Arts
Member of the European Academy of Sciences and Arts

Overview

Bernhard Schölkopf is affiliated with the Max Planck Institute for Intelligent Systems in Germany. Their research contributions are deeply embedded in the field of computer science, with a particular focus on artificial intelligence and machine learning.

The scientist's recent publications include:

Towards Total Recall in Industrial Anomaly Detection, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Toward Causal Representation Learning, 2021, Proceedings of the IEEE
A whole-body FDG-PET/CT Dataset with manually annotated Tumor Lesions, 2022, Scientific Data
Causality for Machine Learning, 2022, ACM eBooks
A Survey of Algorithmic Recourse: Contrastive Explanations and Consequential Recommendations, 2022, ACM Computing Surveys

Frequently collaborating co-authors include:

Julius von Kügelgen (47 joint publications)
Francesco Locatello (40 joint publications)
Stefan Bauer (25 joint publications)
Mrinmaya Sachan (23 joint publications)
Michel Besserve (22 joint publications)

Publications are often featured in venues such as:

arXiv (Cornell University) with 278 publications
Zenodo (CERN European Organization for Nuclear Research) with 14 publications
Repository for Publications and Research Data (ETH Zurich) with 4 publications
Proceedings of the AAAI Conference on Artificial Intelligence with 4 publications
bioRxiv (Cold Spring Harbor Laboratory) with 4 publications

Their scholarly work covers a range of interdisciplinary subfields, including:

Artificial Intelligence
Computer Vision and Pattern Recognition
Molecular Biology
Statistics and Probability
Control and Systems Engineering

Key research topics associated with their work include:

Domain Adaptation and Few-Shot Learning
Bayesian Modeling and Causal Inference
Explainable Artificial Intelligence (XAI)
Adversarial Robustness in Machine Learning
Reinforcement Learning in Robotics
Generative Adversarial Networks and Image Synthesis
Machine Learning and Algorithms

Bernhard Schölkopf is also the author of the book Handbook of Statistical Bioinformatics, published by Springer International Publishing in 2022.

The awards and recognitions received include:

BBVA Foundation Frontiers of Knowledge Award, 2019
ACM Fellow, 2017, for contributions to the theory and practice of machine learning
German National Academy of Sciences Leopoldina - Deutsche Akademie der Naturforscher Leopoldina - Nationale Akademie der Wissenschaften, 2016 (Informatics)
Max Planck Research Award, 2011 (Intelligent systems)
IAPR J. K. Aggarwal Prize, 2006, for advancing the field of kernel methods and showing its wide applicability to pattern recognition problems
Member of the European Academy of Sciences and Arts

Best Publications

Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond

Bernhard Scholkopf;Alexander J. Smola

16004
Citations
A tutorial on support vector regression

Alex J. Smola;Bernhard Schölkopf

15872
Citations
Nonlinear component analysis as a kernel eigenvalue problem

Bernhard Schölkopf;Alexander Smola;Klaus-Robert Müller

10990
Citations
Estimating the Support of a High-Dimensional Distribution

Bernhard Schölkopf;John C. Platt;John C. Shawe-Taylor;Alex J. Smola

7284
Citations
Support vector machines

M.A. Hearst;S.T. Dumais;E. Osman;J. Platt

7011
Citations
Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) [Book reviews]

O. Chapelle;B. Scholkopf;A. Zien

6709
Citations
Advances in kernel methods: support vector learning

Bernhard Schölkopf;Christopher J. C. Burges;Alexander J. Smola

6522
Citations
Learning with kernels

Bernhard Schölkopf

6458
Citations
An introduction to kernel-based learning algorithms

K.-R. Muller;S. Mika;G. Ratsch;K. Tsuda

4962
Citations
Learning with Local and Global Consistency

Dengyong Zhou;Olivier Bousquet;Thomas N. Lal;Jason Weston

4928
Citations
New Support Vector Algorithms

Bernhard Schölkopf;Alex J. Smola;Robert C. Williamson;Peter L. Bartlett

3981
Citations
Fisher discriminant analysis with kernels

S. Mika;G. Ratsch;J. Weston;B. Scholkopf

3815
Citations
Kernel Principal Component Analysis

Bernhard Schölkopf;Alex J. Smola;Klaus-Robert Müller

3235
Citations
A kernel two-sample test

Arthur Gretton;Karsten M. Borgwardt;Malte J. Rasch;Bernhard Schölkopf

3126
Citations
Support vector learning

B Schölkopf

2751
Citations
Kernel methods in machine learning

Thomas Hofmann;Bernhard Schölkopf;Alexander J. Smola

2678
Citations
Support Vector Method for Novelty Detection

Bernhard Schölkopf;Robert C Williamson;Alex J. Smola;John Shawe-Taylor

2563
Citations
A Kernel Method for the Two-Sample-Problem

Arthur Gretton;Karsten M. Borgwardt;Malte Rasch;Bernhard Schölkopf

2177
Citations
A Generalized Representer Theorem

Bernhard Schölkopf;Bernhard Schölkopf;Ralf Herbrich;Ralf Herbrich;Alex J. Smola

2052
Citations
Correcting Sample Selection Bias by Unlabeled Data

Jiayuan Huang;Arthur Gretton;Karsten M. Borgwardt;Bernhard Schölkopf

1947
Citations
Greedy Layer-Wise Training of Deep Networks

Bernhard Schölkopf;John Platt;Thomas Hofmann

93
Citations
WILLIAMSON, ESTIMATING THE SUPPORT OF A HIGH-DIMENSIONAL DISTRIBUTION

B Scholkopf;J C Platt;J Shawe Taylor

25
Citations
Analysis of Representations for Domain Adaptation

Bernhard Schölkopf;John Platt;Thomas Hofmann

5
Citations

Frequent Co-Authors

Thomas Hofmann ETH Zurich

John Platt Google (United States)

Alexander J. Smola Amazon (United States)

Dominik Janzing Amazon (United States)

Arthur Gretton University College London

Gunnar Rätsch ETH Zurich

Jan Peters Technical University of Darmstadt

Kun Zhang Carnegie Mellon University

Stefan Harmeling TU Dortmund University

Felix A. Wichmann University of Tübingen

External Links

Wikipedia of Bernhard Schölkopf Personal website of Bernhard Schölkopf Google Scholar page

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