Sue Ann Campbell
- Statistical and Nonlinear Physics top 0.5%
- stochastic dynamics and bifurcation 27
- Computer Networks and Communications top 0.5%
- Nonlinear Dynamics and Pattern Formation 37
- Neural Networks Stability and Synchronization 16
- Modeling and Simulation top 2%
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function 27
- Geometry and Topology top 5%
- Advanced Differential Equations and Dynamical Systems 6
-
- Mathematical and Theoretical Epidemiology and Ecology Models 11
-
- Evolution and Genetic Dynamics 5
-
- Stability and Controllability of Differential Equations 4
Sue Ann Campbell
71 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 129
- Statistical and Nonlinear Physics 1.1k
- Computer Networks and Communications 1.5k
- Modeling and Simulation 154
- Cognitive Neuroscience 492
- Geometry and Topology 186
Countries citing papers authored by Sue Ann Campbell
This map shows the geographic impact of Sue Ann Campbell'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 Sue Ann Campbell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sue Ann Campbell more than expected).
Fields of papers citing papers by Sue Ann Campbell
This network shows the impact of papers produced by Sue Ann Campbell. 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 Sue Ann Campbell. The network helps show where Sue Ann Campbell may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sue Ann Campbell, 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 | 2024 | 4 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2020 | 7 | |
| 6 | 2019 | 2 | |
| 7 | 2019 | 3 | |
| 8 | 2017 | 8 | |
| 9 | 2015 | 11 | |
| 10 | 2013 | 20 | |
| 11 | 2013 | 13 | |
| 12 | 2013 | 20 | |
| 13 | 2009 | 11 | |
| 14 | 2006 | 43 | |
| 15 | 2005 | 20 | |
| 16 | 2004 | 16 | |
| 17 | 2003 | 195 | |
| 18 | 2001 | 36 | |
| 19 | 1996 | 165 | |
| 20 | 1994 | 150 |
About Sue Ann Campbell
Sue Ann Campbell is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Cognitive Neuroscience, having authored 74 papers that have together received 2.7k indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (37 papers), Neural dynamics and brain function (27 papers), stochastic dynamics and bifurcation (27 papers), Neural Networks Stability and Synchronization (16 papers), Mathematical and Theoretical Epidemiology and Ecology Models (11 papers), Advanced Differential Equations and Dynamical Systems (6 papers), Evolution and Genetic Dynamics (5 papers) and Stability and Controllability of Differential Equations (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.1k citations), Computer Networks and Communications (1.5k citations) and Modeling and Simulation (154 citations). Sue Ann Campbell has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Jacques Bélair, P. van den Driessche, Sehjeong Kim, Xinzhi Liu, Huaiping Zhu, Gail S. K. Wolkowicz, Yuan Yuan, John Milton, Philip Holmes and Toru Ohira. Their work appears in journals such as Journal of Neurophysiology, The FASEB Journal and Neuroscience.
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.