Felix Bießmann
- Health Informatics top 0.5%
- Cognitive Neuroscience top 1%
- Neural dynamics and brain function 10
- EEG and Brain-Computer Interfaces 7
- Functional Brain Connectivity Studies 5
- Signal Processing top 5%
- Artificial Intelligence top 2%
- Machine Learning and Data Classification 7
- Machine Learning and Algorithms 4
- Anomaly Detection Techniques and Applications 4
- Neural Networks and Applications 4
- Human-Computer Interaction top 5%
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- Data Quality and Management 7
- Co-authors
- Frank C. MeineckeSven DähneJohn–Dylan HaynesKai GörgenBenjamin BlankertzStefan HaufePhilipp SchmidtSebastian Schelter
- Journals
- SHILAP Revista de lepidopterología (2 papers)NeuroImage (3 papers)Radiology (1 paper)
- Partner nations
- GermanyUnited StatesSouth Korea
In The Last Decade
Felix Bießmann
45 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 162
- Health Informatics 169
- Cognitive Neuroscience 1.3k
- Signal Processing 202
- Artificial Intelligence 590
- Human-Computer Interaction 91
Countries citing papers authored by Felix Bießmann
This map shows the geographic impact of Felix Bießmann'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 Felix Bießmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Felix Bießmann more than expected).
Fields of papers citing papers by Felix Bießmann
This network shows the impact of papers produced by Felix Bießmann. 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 Felix Bießmann. The network helps show where Felix Bießmann may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Felix Bießmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 7 | |
| 6 | 2023 | 10 | |
| 7 | 2023 | 18 | |
| 8 | 2023 | 61 | |
| 9 | 2023 | 9 | |
| 10 | 2023 | 3 | |
| 11 | 2021 | 149 | |
| 12 | 2021 | 117 | |
| 13 | DataWig: Missing Value Imputation for Tables | 2019 | 67 |
| 14 | On Challenges in Machine Learning Model Management | 2015 | 85 |
| 15 | On the interpretation of weight vectors of linear models in multivariate neuroimagingbreakdown → | 2013 | 850 |
| 16 | 2012 | 19 | |
| 17 | 2012 | 35 | |
| 18 | 2011 | 114 | |
| 19 | 2010 | 57 | |
| 20 | Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance | 2008 | 40 |
About Felix Bießmann
Felix Bießmann is a scholar working on Health Informatics, Cognitive Neuroscience and Signal Processing, having authored 50 papers that have together received 2.5k indexed citations. Recurring topics across this work include Neural dynamics and brain function (10 papers), Machine Learning and Data Classification (7 papers), EEG and Brain-Computer Interfaces (7 papers), Data Quality and Management (7 papers), Functional Brain Connectivity Studies (5 papers), Machine Learning and Algorithms (4 papers), Anomaly Detection Techniques and Applications (4 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Health Informatics (169 citations), Cognitive Neuroscience (1.3k citations) and Signal Processing (202 citations). Felix Bießmann has collaborated with scholars based in Germany, United States and South Korea. Frequent co-authors include Frank C. Meinecke, Sven Dähne, John–Dylan Haynes, Kai Görgen, Benjamin Blankertz, Stefan Haufe, Philipp Schmidt, Sebastian Schelter, Timm Teubner and Klaus‐Robert Müller. Their work appears in journals such as SHILAP Revista de lepidopterología, NeuroImage and Radiology.
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.