Andreas Wichert
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Cognitive Neuroscience
- Management Science and Operations Research top 5%
- Information Systems top 10%
- Co-authors
- Catarina MoreiraLuísa CoheurJoão SilvaAna Cristina MendesFriedrich T. SommerHubertus FeußnerJoão SacramentoPeter Bruza
- Topics
- Neural Networks and Applications (19 papers)Neural dynamics and brain function (12 papers)Quantum Computing Algorithms and Architecture (11 papers)
- Partner nations
- PortugalGermanyUnited Kingdom
In The Last Decade
Andreas Wichert
70 papers receiving 695 citations
Peers
Comparison fields: 5 of 109
- Artificial Intelligence 456
- Computer Vision and Pattern Recognition 106
- Cognitive Neuroscience 102
- Management Science and Operations Research 96
- Information Systems 71
Countries citing papers authored by Andreas Wichert
This map shows the geographic impact of Andreas Wichert'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 Wichert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Wichert more than expected).
Fields of papers citing papers by Andreas Wichert
This network shows the impact of papers produced by Andreas Wichert. 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 Wichert. The network helps show where Andreas Wichert may publish in the future.
Co-authorship network of co-authors of Andreas Wichert
This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Wichert. A scholar is included among the top collaborators of Andreas Wichert 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 Wichert. Andreas Wichert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 25 | |
| 9 | 11 | |
| 10 | 16 | |
| 11 | 1 | |
| 12 | 2 | |
| 13 | 4 | |
| 14 | 11 | |
| 15 | 18 | |
| 16 | Theories, data analysis, and simulation models in neuroimaging: an overview | 1 |
| 17 | Exploratory analysis and data modeling in functional neuroimaging | 43 |
| 18 | Exploratory analysis of event-related fMRI demonstrated in a working memory study | 3 |
| 19 | Audio-visual sensor fusion with neural architectures. | 1 |
| 20 | Neural architectures for sensorfusion in speechrecognition. | 4 |
About Andreas Wichert
Andreas Wichert is a scholar working on General Decision Sciences, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 77 papers that have together received 745 indexed citations. Recurring topics across this work include Neural Networks and Applications (19 papers), Neural dynamics and brain function (12 papers) and Quantum Computing Algorithms and Architecture (11 papers). The work is most often cited by research in Artificial Intelligence (456 citations), General Decision Sciences (26 citations) and Management Science and Operations Research (96 citations). Andreas Wichert has collaborated with scholars based in Portugal, Germany and United Kingdom. Frequent co-authors include Catarina Moreira, Luísa Coheur, João Silva, Ana Cristina Mendes, Friedrich T. Sommer, Hubertus Feußner, João Sacramento, Peter Bruza, Luís Tarrataca and Heiner Bubb. Their work appears in journals such as PLoS ONE, NeuroImage and Expert Systems with Applications.
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.