Martin Bogdan

3.8k total citations
103 papers, 2.6k citations indexed

About

Martin Bogdan is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Martin Bogdan has authored 103 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Cognitive Neuroscience, 31 papers in Cellular and Molecular Neuroscience and 24 papers in Artificial Intelligence. Recurrent topics in Martin Bogdan's work include EEG and Brain-Computer Interfaces (51 papers), Neuroscience and Neural Engineering (29 papers) and Neural dynamics and brain function (27 papers). Martin Bogdan is often cited by papers focused on EEG and Brain-Computer Interfaces (51 papers), Neuroscience and Neural Engineering (29 papers) and Neural dynamics and brain function (27 papers). Martin Bogdan collaborates with scholars based in Germany, Italy and United States. Martin Bogdan's co-authors include Wolfgang Rosenstiel, Niels Birbaumer, Martin Spüler, Thilo Hinterberger, Michael Schröder, Bernhard Schölkopf, Andrea Kübler, Armin Walter, TN Lal and Jason Weston and has published in prestigious journals such as PLoS ONE, NeuroImage and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Martin Bogdan

93 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Bogdan Germany 27 1.9k 785 352 351 342 103 2.6k
Sung Chan Jun South Korea 26 1.9k 1.0× 765 1.0× 556 1.6× 415 1.2× 243 0.7× 123 2.9k
Damien Coyle United Kingdom 30 2.6k 1.4× 1.1k 1.4× 503 1.4× 312 0.9× 432 1.3× 149 3.2k
Ian Daly United Kingdom 31 2.7k 1.4× 973 1.2× 533 1.5× 351 1.0× 596 1.7× 103 3.1k
Stéphane Bonnet France 20 1.4k 0.7× 403 0.5× 335 1.0× 392 1.1× 284 0.8× 78 2.2k
Yangsong Zhang China 32 2.3k 1.2× 650 0.8× 388 1.1× 313 0.9× 365 1.1× 100 3.1k
Bruno Arnaldi France 19 1.9k 1.0× 717 0.9× 382 1.1× 250 0.7× 499 1.5× 70 2.8k
Ou Bai United States 28 2.8k 1.5× 969 1.2× 296 0.8× 692 2.0× 234 0.7× 123 3.8k
Christian Kothe United States 17 3.2k 1.6× 612 0.8× 237 0.7× 287 0.8× 325 1.0× 36 3.6k
R. Leeb Switzerland 20 2.2k 1.1× 896 1.1× 355 1.0× 340 1.0× 466 1.4× 27 2.4k
Moritz Grosse‐Wentrup Germany 21 2.0k 1.0× 836 1.1× 370 1.1× 265 0.8× 370 1.1× 78 2.3k

Countries citing papers authored by Martin Bogdan

Since Specialization
Citations

This map shows the geographic impact of Martin Bogdan'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 Martin Bogdan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Bogdan more than expected).

Fields of papers citing papers by Martin Bogdan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Bogdan. 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 Martin Bogdan. The network helps show where Martin Bogdan may publish in the future.

Co-authorship network of co-authors of Martin Bogdan

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Bogdan. A scholar is included among the top collaborators of Martin Bogdan 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 Martin Bogdan. Martin Bogdan 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.
Bogdan, Martin, et al.. (2025). The Reinforced Liquid State Machine: A New Training Architecture for Spiking Neural Networks. 699–704. 1 indexed citations
2.
Bogdan, Martin, et al.. (2025). A bimodal image dataset for seed classification from the visible and near-infrared spectrum. Scientific Data. 12(1). 1629–1629.
4.
Bogdan, Martin, et al.. (2022). Application of Soft-Clustering to Assess Consciousness in a CLIS Patient. Brain Sciences. 13(1). 65–65. 4 indexed citations
5.
Wu, Shang‐Ju, et al.. (2022). Extendable Hybrid Approach to Detect Conscious States in a CLIS Patient Using Machine Learning. SNE Simulation Notes Europe. 32(1). 37–45. 4 indexed citations
6.
Wu, Shang‐Ju, Nicoletta Nicolaou, & Martin Bogdan. (2020). Consciousness Detection in a Complete Locked-in Syndrome Patient through Multiscale Approach Analysis. Entropy. 22(12). 1411–1411. 7 indexed citations
7.
Gundlach, Christopher, et al.. (2020). Transient Amplitude Modulation of Alpha-Band Oscillations by Short-Time Intermittent Closed-Loop tACS. Frontiers in Human Neuroscience. 14. 366–366. 28 indexed citations
8.
Bogdan, Martin, et al.. (2018). Neural Networks for Implicit Feedback Datasets.. The European Symposium on Artificial Neural Networks. 1 indexed citations
9.
Bogdan, Martin, et al.. (2017). Collaborative filtering with neural networks.. The European Symposium on Artificial Neural Networks. 2 indexed citations
10.
Pelz, Georg, et al.. (2015). Bordersearch: an adaptive identification of failure regions. Design, Automation, and Test in Europe. 1036–1041. 8 indexed citations
11.
Rosenstiel, Wolfgang, et al.. (2013). Rapid Design Space Exploration of a State-of-the-art PSI 5 Controller.. 3–12. 3 indexed citations
12.
Walter, Armin, Georgios Naros, Martin Spüler, et al.. (2013). Decoding stimulation intensity from evoked ECoG activity using support vector regression.. The European Symposium on Artificial Neural Networks. 1 indexed citations
13.
Spüler, Martin, Michael Bensch, Sonja C. Kleih, et al.. (2012). Online use of error-related potentials in healthy users and people with severe motor impairment increases performance of a P300-BCI. Clinical Neurophysiology. 123(7). 1328–1337. 111 indexed citations
14.
Walter, Carina, Gabriele Cierniak, Peter Gerjets, Wolfgang Rosenstiel, & Martin Bogdan. (2011). Classifying mental states with machine learning algorithms using alpha activity decline.. The European Symposium on Artificial Neural Networks. 3 indexed citations
15.
Butovas, Sergejus, et al.. (2008). Direct and inverse solution for a stimulus adaptation problem using SVR. The European Symposium on Artificial Neural Networks. 397–402. 4 indexed citations
16.
Bensch, Michael, Michael Schröder, Martin Bogdan, & Wolfgang Rosenstiel. (2005). Feature Selection for High-Dimensional Industrial Data. The European Symposium on Artificial Neural Networks. 375–380. 9 indexed citations
17.
Schwarz, Cornelius, et al.. (2004). Employing ICA and SOM for spike sorting of multielectrode recordings from CNS. Journal of Physiology-Paris. 98(4-6). 349–356. 20 indexed citations
18.
Lal, TN, Michael Schröder, Thilo Hinterberger, et al.. (2004). Support Vector Channel Selection in BCI. IEEE Transactions on Biomedical Engineering. 51(6). 1003–1010. 387 indexed citations
19.
Bogdan, Martin, Michael Schröder, & Wolfgang Rosenstiel. (2003). Towards the restoration of hand grasp function of quadriplegic patients based on an artificial neural net controller using peripheral nerve stimulation - an approach. The European Symposium on Artificial Neural Networks. 427–438.
20.
Bogdan, Martin & Wolfgang Rosenstiel. (2001). Detection of cluster in Self-Organizing Maps for controlling a prostheses using nerve signals.. The European Symposium on Artificial Neural Networks. 50(1). 131–136. 8 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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