Judith Lehnert
- Computer Networks and Communications top 2%
- Statistical and Nonlinear Physics top 2%
- Cognitive Neuroscience top 10%
- Biomedical Engineering
- Molecular Biology
- Co-authors
- Eckehard SchöllThomas DahmsPhilipp HövelАlexander L. FradkovAnton SelivanovValentín FlunkertAnna ZakharovaWolfram Just
- Topics
- Nonlinear Dynamics and Pattern Formation (14 papers)Neural dynamics and brain function (7 papers)stochastic dynamics and bifurcation (6 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputer Networks and CommunicationsCognitive Neuroscience
- Partner nations
- GermanyRussiaUnited Kingdom
In The Last Decade
Judith Lehnert
18 papers receiving 510 citations
Peers
Comparison fields: 5 of 54
- Computer Networks and Communications 450
- Statistical and Nonlinear Physics 289
- Cognitive Neuroscience 150
- Biomedical Engineering 53
- Molecular Biology 45
Countries citing papers authored by Judith Lehnert
This map shows the geographic impact of Judith Lehnert'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 Judith Lehnert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Judith Lehnert more than expected).
Fields of papers citing papers by Judith Lehnert
This network shows the impact of papers produced by Judith Lehnert. 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 Judith Lehnert. The network helps show where Judith Lehnert may publish in the future.
Co-authorship network of co-authors of Judith Lehnert
This figure shows the co-authorship network connecting the top 25 collaborators of Judith Lehnert. A scholar is included among the top collaborators of Judith Lehnert 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 Judith Lehnert. Judith Lehnert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 4 | |
| 3 | 19 | |
| 4 | 22 | |
| 5 | 13 | |
| 6 | 16 | |
| 7 | 12 | |
| 8 | 17 | |
| 9 | 21 | |
| 10 | 39 | |
| 11 | 19 | |
| 12 | 15 | |
| 13 | 88 | |
| 14 | 141 | |
| 15 | 20 | |
| 16 | 9 | |
| 17 | 36 | |
| 18 | 34 |
About Judith Lehnert
Judith Lehnert is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Cognitive Neuroscience, having authored 18 papers that have together received 528 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (14 papers), Neural dynamics and brain function (7 papers) and stochastic dynamics and bifurcation (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (289 citations), Computer Networks and Communications (450 citations) and Cognitive Neuroscience (150 citations). Judith Lehnert has collaborated with scholars based in Germany, Russia and United Kingdom. Frequent co-authors include Eckehard Schöll, Thomas Dahms, Philipp Hövel, Аlexander L. Fradkov, Anton Selivanov, Valentín Flunkert, Anna Zakharova, Wolfram Just, Josef Ladenbauer and Klaus Obermayer. Their work appears in journals such as Physics in Medicine and Biology, Europhysics Letters (EPL) and The European Physical Journal B.
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.