Ekkehard Ullner

1.2k citations
28 papers · 977 · h-index 15

Impact in

Papers in

Ekkehard Ullner

27 papers receiving 946 citations

Peers

Ekkehard Ullner
Comparison fields: 5 of 70
  • Statistical and Nonlinear Physics 639
  • Computer Networks and Communications 644
  • Cognitive Neuroscience 317
  • Modeling and Simulation 25
  • Endocrine and Autonomic Systems 31
Replace E.I. Volkov with:
E.I. Volkov Russia
D. V. Senthilkumar India
Manish Dev Shrimali India
Tanmoy Banerjee India
Aneta Koseska Germany
Per Sebastian Skardal United States
Vivien Kirk New Zealand
Steven M. Baer United States
Mark R. Tinsley United States
Amit Sharma India
Ekkehard Ullner relative to E.I. Volkov Russia E.I. Volkov's profile →
Citations per field
00.5×1.6×
E.I. Volkov · 1×
Citations per year

Countries citing papers authored by Ekkehard Ullner

Since Specialization
Citations

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

Fields of papers citing papers by Ekkehard Ullner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ekkehard Ullner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ekkehard Ullner Line = papers co-authored together Ekkehard Ullner links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007193
2 2003171
3 200989
4 200382
5 200873
6 200359
7 200358
8 200947
9 200333
10 201625
11 200523
12 201120
13 201019
14 201818
15 202017
16 200612
17 20147
18 20216
19 20145
20 20204

About Ekkehard Ullner

Ekkehard Ullner is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications, Cognitive Neuroscience, Molecular Biology and Genetics, having authored 28 papers that have together received 977 indexed citations. Recurring topics across this work include stochastic dynamics and bifurcation (18 papers), Nonlinear Dynamics and Pattern Formation (17 papers), Neural dynamics and brain function (11 papers), Gene Regulatory Network Analysis (8 papers), Evolution and Genetic Dynamics (3 papers), Ecosystem dynamics and resilience (3 papers), Advanced Thermodynamics and Statistical Mechanics (1 paper) and Circadian rhythm and melatonin (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (639 citations), Computer Networks and Communications (644 citations), Cognitive Neuroscience (317 citations), Modeling and Simulation (25 citations) and Endocrine and Autonomic Systems (31 citations). Ekkehard Ullner has collaborated with scholars based in United Kingdom, Germany and Spain. Frequent co-authors include Jordi García‐Ojalvo, Alexey Zaikin, Jürgen Kurths, Evgenii Volkov, E.I. Volkov, Aneta Koseska, Antonio Politi, Javier Buceta, Hölger Kantz and Antoni Dı́ez-Noguera. Their work appears in journals such as PLoS ONE, Chaos An Interdisciplinary Journal of Nonlinear Science, Physical Review Letters, The European Physical Journal Special Topics and Physics Letters A.

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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