World's Best Scientists 2026 revealed!
Award Badge
Computer Science
Germany
2026

D-Index & Metrics

Computer Science

D-Index
161
Citations
140992
World Ranking
21
National Ranking
3

Research.com Recognitions

  • 2026 - Research.com Computer Science in Germany Leader 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

Overview

Klaus-Robert Müller is a researcher affiliated with the Technical University of Berlin in Germany. Their academic focus spans multiple fields with an emphasis on artificial intelligence and its applications in medicine and materials science.

Their recent works include a range of publications addressing explainable artificial intelligence, machine learning methods, and medical imaging. Notable papers are:

  • Higher-Order Explanations of Graph Neural Networks via Relevant Walks, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Mammography Image Quality Assurance Using Deep Learning, 2020, IEEE Transactions on Biomedical Engineering
  • Fairwashing Explanations with Off-Manifold Detergent, 2020, arXiv (Cornell University)
  • Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology, 2021, Preprints.org
  • Decoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligence, 2025, Nature Cancer

Their research contributions cover several key fields of study:

  • Computer Science
  • Medicine

Within these fields, subfields that receive particular attention include:

  • Artificial Intelligence
  • Materials Chemistry
  • Oncology
  • Radiology, Nuclear Medicine and Imaging
  • Computational Theory and Mathematics

Müller's work addresses various specialized topics including:

  • Explainable Artificial Intelligence (XAI)
  • Machine Learning in Materials Science
  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Computational Drug Discovery Methods
  • Cancer Treatment and Pharmacology
  • Machine Learning and Data Classification

Their frequent coauthors include:

  • Grégoire Montavon
  • Shinichi Nakajima
  • Frederick Klauschen
  • Lukas Ruff
  • Gabriel Dernbach

Publications by Klaus-Robert Müller are commonly found in the following venues:

  • arXiv (Cornell University)
  • Annals of Oncology
  • ESMO Open
  • Chemical Science
  • Nature Communications

Best Publications

  • Nonlinear component analysis as a kernel eigenvalue problem

    Bernhard Schölkopf;Alexander Smola;Klaus-Robert Müller

  • An introduction to kernel-based learning algorithms

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

  • On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation.

    Sebastian Bach;Alexander Binder;Grégoire Montavon;Frederick Klauschen

  • Efficient BackProp

    Yann LeCun;Léon Bottou;Genevieve B. Orr;Klaus-Robert Müller

  • Efficient BackProp

    Unknown

  • Kernel Principal Component Analysis

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

  • Methods for interpreting and understanding deep neural networks

    Grégoire Montavon;Wojciech Samek;Klaus Robert Müller;Klaus Robert Müller;Klaus Robert Müller

  • Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

    Matthias Rupp;Matthias Rupp;Alexandre Tkatchenko;Alexandre Tkatchenko;Klaus Robert Müller;Klaus Robert Müller;O. Anatole Von Lilienfeld;O. Anatole Von Lilienfeld

  • Optimizing Spatial filters for Robust EEG Single-Trial Analysis

    B. Blankertz;R. Tomioka;S. Lemm;M. Kawanabe

  • SchNet - A deep learning architecture for molecules and materials.

    Kristof T. Schütt;Huziel E. Sauceda;P. J. Kindermans;Alexandre Tkatchenko

  • Soft Margins for AdaBoost

    G. Rätsch;T. Onoda;K.-R. Müller

  • Input space versus feature space in kernel-based methods

    B. Scholkopf;S. Mika;C.J.C. Burges;P. Knirsch

  • Explaining nonlinear classification decisions with deep Taylor decomposition

    Grégoire Montavon;Sebastian Lapuschkin;Alexander Binder;Wojciech Samek

  • Predicting Time Series with Support Vector Machines

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

  • A Unifying Review of Deep and Shallow Anomaly Detection

    Lukas Ruff;Jacob R. Kauffmann;Robert A. Vandermeulen;Gregoire Montavon

  • Kernel PCA and De-Noising in Feature Spaces

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

  • Single-Trial Analysis and Classification of ERP Components - a Tutorial

    Benjamin Blankertz;Steven Lemm;Matthias Sebastian Treder;Stefan Haufe

  • Unmasking Clever Hans predictors and assessing what machines really learn.

    Sebastian Lapuschkin;Stephan Wäldchen;Alexander Binder;Grégoire Montavon

  • Explainable artificial intelligence: Understanding, visualizing and interpreting deep learning models

    Wojciech Samek;Thomas Wiegand;Klaus-Robert Müller

  • Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data

    Felix Sattler;Simon Wiedemann;Klaus-Robert Muller;Wojciech Samek

  • Evaluating the Visualization of What a Deep Neural Network Has Learned

    Wojciech Samek;Alexander Binder;Gregoire Montavon;Sebastian Lapuschkin

  • The non-invasive Berlin Brain-Computer Interface: fast acquisition of effective performance in untrained subjects.

    Benjamin Blankertz;Guido Dornhege;Matthias Krauledat;Klaus Robert Müller

  • The BCI competition III: validating alternative approaches to actual BCI problems

    B. Blankertz;K.-R. Muller;D.J. Krusienski;G. Schalk

  • Robust and Communication-Efficient Federated Learning from Non-IID Data

    Felix Sattler;Simon Wiedemann;Klaus-Robert Müller;Wojciech Samek

Frequent Co-Authors

Benjamin Blankertz
Benjamin Blankertz Technical University of Berlin
Grégoire Montavon
Grégoire Montavon Freie Universität Berlin
Wojciech Samek
Wojciech Samek Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute
Thomas Wiegand
Thomas Wiegand Technical University of Berlin
Motoaki Kawanabe
Motoaki Kawanabe Advanced Telecommunications Research Institute International
Alexandre Tkatchenko
Alexandre Tkatchenko University of Luxembourg
Gabriel Curio
Gabriel Curio Charité - University Medicine Berlin
Gunnar Rätsch
Gunnar Rätsch ETH Zurich
José del R. Millán
José del R. Millán The University of Texas at Austin
Matthias Rupp
Matthias Rupp Luxembourg Institute of Science and Technology

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

Exploring Computer Science in the USA opens doors to many flexible study and career options. For those looking to enter the workforce quickly, consider one of the shortest associate degree program choices available online. These programs offer a fast-track to foundational skills and entry-level tech jobs.

If you’re interested in top-tier credentials, earning a degree from one of the highly accredited online universities ensures your education meets quality standards recognized nationwide. Accreditation matters for both job prospects and further studies.

For aspiring educators considering advanced roles, it’s worth researching how much does a doctorate in education cost, especially since costs can vary widely and there are affordable online options.

Interested in the creative side of tech? Dive into the gaming industry by exploring an online game development degree. These specialized programs prepare you for exciting careers in game design and interactive media.

Best Scientists Citing Klaus-Robert Müller

Trending Scientists