Viola Priesemann
- Cognitive Neuroscience top 1%
- Cellular and Molecular Neuroscience top 5%
- Modeling and Simulation top 0.5%
- Statistical and Nonlinear Physics top 2%
- Economics and Econometrics top 5%
- Co-authors
- Michael WibralJoseph T. LizierJohannes ZierenbergJonas DehningF. Paul SpitznerJoão Pinheiro NetoMichael WilczekJens Wilting
- Topics
- Neural dynamics and brain function (41 papers)COVID-19 epidemiological studies (16 papers)Functional Brain Connectivity Studies (15 papers)
- Partner nations
- GermanyUnited KingdomAustralia
In The Last Decade
Viola Priesemann
65 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 161
- Cognitive Neuroscience 1.9k
- Cellular and Molecular Neuroscience 585
- Modeling and Simulation 532
- Statistical and Nonlinear Physics 402
- Economics and Econometrics 329
Countries citing papers authored by Viola Priesemann
This map shows the geographic impact of Viola Priesemann'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 Viola Priesemann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Viola Priesemann more than expected).
Fields of papers citing papers by Viola Priesemann
This network shows the impact of papers produced by Viola Priesemann. 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 Viola Priesemann. The network helps show where Viola Priesemann may publish in the future.
Co-authorship network of co-authors of Viola Priesemann
This figure shows the co-authorship network connecting the top 25 collaborators of Viola Priesemann. A scholar is included among the top collaborators of Viola Priesemann 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 Viola Priesemann. Viola Priesemann 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 | 3 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 14 | |
| 7 | 20 | |
| 8 | 24 | |
| 9 | 4 | |
| 10 | 7 | |
| 11 | 4 | |
| 12 | 3 | |
| 13 | 7 | |
| 14 | 27 | |
| 15 | 5 | |
| 16 | Inferring change points in the spread of COVID-19 reveals the effectiveness of interventionsbreakdown → | 517 |
| 17 | Inferring collective dynamical states from subsampled systems | 1 |
| 18 | 62 | |
| 19 | 192 | |
| 20 | 176 |
About Viola Priesemann
Viola Priesemann is a scholar working on Modeling and Simulation, Cognitive Neuroscience and Statistical and Nonlinear Physics, having authored 70 papers that have together received 3.2k indexed citations. Recurring topics across this work include Neural dynamics and brain function (41 papers), COVID-19 epidemiological studies (16 papers) and Functional Brain Connectivity Studies (15 papers). The work is most often cited by research in Modeling and Simulation (532 citations), Cognitive Neuroscience (1.9k citations) and Statistical and Nonlinear Physics (402 citations). Viola Priesemann has collaborated with scholars based in Germany, United Kingdom and Australia. Frequent co-authors include Michael Wibral, Joseph T. Lizier, Johannes Zierenberg, Jonas Dehning, F. Paul Spitzner, João Pinheiro Neto, Michael Wilczek, Jens Wilting, Raúl Vicente and Michael Lindner. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and The Lancet.
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.