Michael Schmuker

2.7k total citations
49 papers, 1.4k citations indexed

About

Michael Schmuker is a scholar working on Cellular and Molecular Neuroscience, Biomedical Engineering and Sensory Systems. According to data from OpenAlex, Michael Schmuker has authored 49 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Cellular and Molecular Neuroscience, 17 papers in Biomedical Engineering and 16 papers in Sensory Systems. Recurrent topics in Michael Schmuker's work include Neurobiology and Insect Physiology Research (18 papers), Advanced Chemical Sensor Technologies (17 papers) and Olfactory and Sensory Function Studies (16 papers). Michael Schmuker is often cited by papers focused on Neurobiology and Insect Physiology Research (18 papers), Advanced Chemical Sensor Technologies (17 papers) and Olfactory and Sensory Function Studies (16 papers). Michael Schmuker collaborates with scholars based in Germany, United Kingdom and Australia. Michael Schmuker's co-authors include Gisbert Schneider, Michael Meißner, Martin Paul Nawrot, Stuart A. Ralph, Geoffrey I. McFadden, Thomas Pfeil, Thomas Nowotny, Narayan Srinivasa, Evangelos Eleftheriou and Bipin Rajendran and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Angewandte Chemie International Edition and NeuroImage.

In The Last Decade

Michael Schmuker

48 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Schmuker Germany 19 471 439 259 231 206 49 1.4k
Dominique Martinez France 22 356 0.8× 329 0.7× 187 0.7× 289 1.3× 102 0.5× 103 1.5k
Tim Pearce United Kingdom 18 282 0.6× 564 1.3× 133 0.5× 1.1k 4.9× 67 0.3× 60 1.8k
R. Andrew Russell Australia 27 417 0.9× 116 0.3× 104 0.4× 1.0k 4.4× 62 0.3× 89 2.1k
Francisco B. Rodrı́guez Spain 17 146 0.3× 156 0.4× 245 0.9× 133 0.6× 97 0.5× 90 992
Jen‐Wei Lin United States 23 1.1k 2.3× 60 0.1× 28 0.1× 68 0.3× 1.1k 5.5× 76 2.1k
Wei Gong China 24 272 0.6× 270 0.6× 134 0.5× 634 2.7× 277 1.3× 104 1.9k
Stephen M. Plaza United States 16 302 0.6× 397 0.9× 69 0.3× 11 0.0× 67 0.3× 30 834
Naomi Harte Ireland 17 76 0.2× 35 0.1× 341 1.3× 91 0.4× 1.4k 6.8× 98 3.2k
Sungmin Hwang South Korea 26 419 0.9× 1.2k 2.8× 189 0.7× 354 1.5× 444 2.2× 166 2.6k
Hai Nguyen United States 19 90 0.2× 53 0.1× 128 0.5× 128 0.6× 114 0.6× 41 1.1k

Countries citing papers authored by Michael Schmuker

Since Specialization
Citations

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

Fields of papers citing papers by Michael Schmuker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Schmuker

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Schmuker. A scholar is included among the top collaborators of Michael Schmuker 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 Michael Schmuker. Michael Schmuker 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.
Schaik, André van, et al.. (2025). Neuromorphic principles for machine olfaction. Neuromorphic Computing and Engineering. 5(2). 23001–23001. 1 indexed citations
2.
Schmuker, Michael, et al.. (2025). A Neuromorphic Electronic Nose Design. IEEE Sensors Journal. 25(12). 23135–23143. 1 indexed citations
3.
Steuber, Volker, et al.. (2025). Computational modelling of olfactory receptors. Biochimica et Biophysica Acta (BBA) - General Subjects. 1869(8). 130825–130825. 1 indexed citations
4.
Schaik, André van, et al.. (2024). Limitations in odour recognition and generalization in a neuromorphic olfactory circuit. Nature Machine Intelligence. 6(12). 1451–1453. 4 indexed citations
5.
Ackels, Tobias, et al.. (2024). High-speed odor sensing using miniaturized electronic nose. Science Advances. 10(45). eadp1764–eadp1764. 24 indexed citations
6.
Sutton, Samuel, et al.. (2024). Odour Localization in Neuromorphic Systems. University of Groningen research database (University of Groningen / Centre for Information Technology). 1–5. 1 indexed citations
7.
Davey, Neil, et al.. (2021). Growth rules for the repair of Asynchronous Irregular neuronal networks after peripheral lesions. PLoS Computational Biology. 17(6). e1008996–e1008996. 2 indexed citations
8.
Schmuker, Michael, et al.. (2021). Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review. Frontiers in Neural Circuits. 15. 610446–610446. 31 indexed citations
9.
Spors, Hartwig, et al.. (2020). Computational exploration of molecular receptive fields in the olfactory bulb reveals a glomerulus-centric chemical map. Scientific Reports. 10(1). 77–77. 8 indexed citations
10.
Schmuker, Michael, et al.. (2019). An unsupervised neuromorphic clustering algorithm. Biological Cybernetics. 113(4). 423–437. 13 indexed citations
11.
Moshourab, Rabih, et al.. (2015). A Probabilistic Model for Estimating the Depth and Threshold Temperature of C-fiber Nociceptors. Scientific Reports. 5(1). 17670–17670. 7 indexed citations
12.
Spors, Hartwig, et al.. (2014). Automatic segmentation of odor maps in the mouse olfactory bulb using regularized non-negative matrix factorization. NeuroImage. 98. 279–288. 12 indexed citations
13.
Sachse, Silke, et al.. (2013). Physicochemical vs. Vibrational Descriptors for Prediction of Odor Receptor Responses. Molecular Informatics. 32(9-10). 855–865. 16 indexed citations
14.
Pfeil, Thomas, Andreas Grübl, Eric Müller, et al.. (2013). Six Networks on a Universal Neuromorphic Computing Substrate. Frontiers in Neuroscience. 7. 11–11. 110 indexed citations
15.
Schmuker, Michael, Nobuhiro Yamagata, Martin Paul Nawrot, & Randolf Menzel. (2011). Parallel Representation of Stimulus Identity and Intensity in a Dual Pathway Model Inspired by the Olfactory System of the Honeybee. PubMed. 4. 17–17. 33 indexed citations
16.
Chen, Yiming, et al.. (2011). A Behavioral Odor Similarity "Space" in Larval Drosophila. Chemical Senses. 36(3). 237–249. 19 indexed citations
17.
Eschbach, Claire, Katrin Vogt, Michael Schmuker, & Bertram Gerber. (2011). The Similarity between Odors and Their Binary Mixtures in Drosophila. Chemical Senses. 36(7). 613–621. 9 indexed citations
18.
Schmuker, Michael, et al.. (2007). Predicting olfactory receptor neuron responses from odorant structure. Chemistry Central Journal. 1(1). 11–11. 40 indexed citations
19.
Schmuker, Michael, et al.. (2006). SOMMER: self-organising maps for education and research. Journal of Molecular Modeling. 13(1). 225–228. 19 indexed citations
20.

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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