Andreas Mueller

6.3k total citations · 2 hit papers
44 papers, 2.5k citations indexed

About

Andreas Mueller is a scholar working on Control and Systems Engineering, Cognitive Neuroscience and Biomedical Engineering. According to data from OpenAlex, Andreas Mueller has authored 44 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Control and Systems Engineering, 12 papers in Cognitive Neuroscience and 11 papers in Biomedical Engineering. Recurrent topics in Andreas Mueller's work include Robotic Mechanisms and Dynamics (8 papers), Attention Deficit Hyperactivity Disorder (7 papers) and EEG and Brain-Computer Interfaces (6 papers). Andreas Mueller is often cited by papers focused on Robotic Mechanisms and Dynamics (8 papers), Attention Deficit Hyperactivity Disorder (7 papers) and EEG and Brain-Computer Interfaces (6 papers). Andreas Mueller collaborates with scholars based in Austria, Germany and United States. Andreas Mueller's co-authors include Gaël Varoquaux, Fabian Pedregosa, Philippe Gervais, Alexandre Gramfort, Jean Kossaifi, Michael Eickenberg, Bertrand Thirion, Alexandre Abraham, Juri D. Kropotov and В. А. Пономарев and has published in prestigious journals such as NeuroImage, Scientific Reports and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Andreas Mueller

42 papers receiving 2.4k citations

Hit Papers

Machine learning for neuroimaging with scikit-learn 2014 2026 2018 2022 2014 2015 400 800 1.2k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Andreas Mueller Austria 14 1.1k 325 300 266 212 44 2.5k
Kay H. Brodersen Switzerland 20 1.6k 1.4× 335 1.0× 237 0.8× 556 2.1× 172 0.8× 27 3.5k
Francisco del Pozo Spain 36 1.6k 1.4× 297 0.9× 382 1.3× 271 1.0× 345 1.6× 164 4.8k
Fabian Pedregosa France 6 939 0.8× 115 0.4× 365 1.2× 220 0.8× 211 1.0× 8 2.0k
Morten Mørup Denmark 26 861 0.8× 152 0.5× 497 1.7× 470 1.8× 189 0.9× 123 3.1k
Andrés Ortíz Spain 29 464 0.4× 250 0.8× 338 1.1× 787 3.0× 123 0.6× 130 2.8k
Kazunori Matsumoto Japan 30 564 0.5× 609 1.9× 202 0.7× 107 0.4× 272 1.3× 204 2.9k
Minjeong Kim United States 30 605 0.5× 326 1.0× 621 2.1× 348 1.3× 202 1.0× 129 2.6k
Dimitris Samaras United States 40 816 0.7× 119 0.4× 418 1.4× 878 3.3× 215 1.0× 149 5.0k
Michael Eickenberg United States 16 1.0k 0.9× 111 0.3× 343 1.1× 217 0.8× 178 0.8× 35 2.1k
Alexandre Abraham France 10 1.6k 1.4× 248 0.8× 577 1.9× 209 0.8× 197 0.9× 32 2.6k

Countries citing papers authored by Andreas Mueller

Since Specialization
Citations

This map shows the geographic impact of Andreas Mueller's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andreas Mueller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Mueller more than expected).

Fields of papers citing papers by Andreas Mueller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andreas Mueller. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andreas Mueller. The network helps show where Andreas Mueller may publish in the future.

Co-authorship network of co-authors of Andreas Mueller

This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Mueller. A scholar is included among the top collaborators of Andreas Mueller based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andreas Mueller. Andreas Mueller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hoffmann, M., et al.. (2025). Remanufacturing production planning and control: Conceptual framework for requirement definition. Econstor (Econstor). 15(1). 97–126. 1 indexed citations
3.
Mueller, Andreas, József Kövecses, Charles C. Kim, Chandramouli Padmanabhan, & Gábor Orosz. (2023). Joint Special Issue: Design and Control of Responsive Robots. Journal of Computational and Nonlinear Dynamics. 18(6). 2 indexed citations
4.
Jindal, Alekh, Brandon Haynes, Carlo Curino, et al.. (2021). Magpie: Python at Speed and Scale using Cloud Backends.. Conference on Innovative Data Systems Research. 9 indexed citations
5.
Ortner, Michael, et al.. (2020). Automatized Insertion of Multipolar Electric Plugs by Means of Force Controlled Industrial Robots. 1465–1472. 4 indexed citations
6.
Kumar, Shivesh, et al.. (2020). An Analytical and Modular Software Workbench for Solving Kinematics and Dynamics of Series-Parallel Hybrid Robots. Journal of Mechanisms and Robotics. 12(2). 21 indexed citations
7.
Gattringer, Hubert, et al.. (2020). Time-Optimal Path Following for Robotic Manipulation of Loosely Placed Objects: Modeling and Experiment. IFAC-PapersOnLine. 53(2). 8450–8455. 5 indexed citations
8.
Kropotov, Juri D., et al.. (2019). Latent ERP components of cognitive dysfunctions in ADHD and schizophrenia. Clinical Neurophysiology. 130(4). 445–453. 16 indexed citations
9.
Mueller, Andreas. (2019). Modern Robotics: Mechanics, Planning, and Control [Bookshelf]. IEEE Control Systems. 39(6). 100–102. 23 indexed citations
10.
Kumar, Shivesh, Carl Julius Martensen, Andreas Mueller, & Frank Kirchner. (2019). Model Simplification For Dynamic Control of Series-Parallel Hybrid Robots - A Representative Study on the Effects of Neglected Dynamics Shivesh. 5701–5708. 6 indexed citations
11.
Mueller, Andreas, et al.. (2018). Flexibility in Upper Limb Rehabilitation With the Use of 1-DOF Fourbar Linkages. 1 indexed citations
12.
Candrian, Gian, et al.. (2017). Facial emotion recognition deficits in children with and without attention deficit hyperactivity disorder. Neuroreport. 28(14). 917–921. 9 indexed citations
13.
Li, Xinwei, et al.. (2017). Computational derivation of a molecular framework for hair follicle biology from disease genes. Scientific Reports. 7(1). 16303–16303. 4 indexed citations
14.
Kompatsiari, Kyveli, Gian Candrian, & Andreas Mueller. (2016). Test-retest reliability of ERP components: A short-term replication of a visual Go/NoGo task in ADHD subjects. Neuroscience Letters. 617. 166–172. 25 indexed citations
15.
Abraham, Alexandre, Fabian Pedregosa, Michael Eickenberg, et al.. (2014). Machine learning for neuroimaging with scikit-learn. Frontiers in Neuroinformatics. 8. 14–14. 1364 indexed citations breakdown →
16.
Пономарев, В. А., Andreas Mueller, Gian Candrian, Vera A. Grin-Yatsenko, & Juri D. Kropotov. (2013). Group Independent Component Analysis (gICA) and Current Source Density (CSD) in the study of EEG in ADHD adults. Clinical Neurophysiology. 125(1). 83–97. 59 indexed citations
17.
Kropotov, Juri D., В. А. Пономарев, Stig Hollup, & Andreas Mueller. (2011). Dissociating action inhibition, conflict monitoring and sensory mismatch into independent components of event related potentials in GO/NOGO task. NeuroImage. 57(2). 565–575. 93 indexed citations
19.
Mueller, Andreas, Gian Candrian, Juri D. Kropotov, В. А. Пономарев, & Gian-Marco Baschera. (2010). Classification of ADHD patients on the basis of independent ERP components using a machine learning system. PubMed. 4(S1). S1–S1. 114 indexed citations
20.
Asmundis, Carlo de, Anna Francesconi, Griet Steurs, et al.. (2009). Leaving out control groups: an internal contrast analysis of gene expression profiles in atrial fibrillation patients - A systems biology approach to clinical categorization. Bioinformation. 3(6). 275–278. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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