Chris G. Antonopoulos
- Statistical and Nonlinear Physics top 2%
- Modeling and Simulation top 0.5%
- Computer Networks and Communications top 5%
- Economics and Econometrics top 5%
- Cognitive Neuroscience top 10%
- Co-authors
- Argha MondalIan A. CooperTassos BountisCh. SkokosMurilo S. BaptistaGeorge PapadopoulosAggeliki PrayatiChristos Koulamas
- Topics
- Nonlinear Dynamics and Pattern Formation (19 papers)Neural dynamics and brain function (14 papers)Quantum chaos and dynamical systems (14 papers)
- Cited by
- Modeling and SimulationStatistical and Nonlinear PhysicsComputer Networks and Communications
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- United KingdomGreeceBrazil
In The Last Decade
Chris G. Antonopoulos
52 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 118
- Statistical and Nonlinear Physics 430
- Modeling and Simulation 399
- Computer Networks and Communications 296
- Economics and Econometrics 162
- Cognitive Neuroscience 161
Countries citing papers authored by Chris G. Antonopoulos
This map shows the geographic impact of Chris G. Antonopoulos'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 Chris G. Antonopoulos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris G. Antonopoulos more than expected).
Fields of papers citing papers by Chris G. Antonopoulos
This network shows the impact of papers produced by Chris G. Antonopoulos. 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 Chris G. Antonopoulos. The network helps show where Chris G. Antonopoulos may publish in the future.
Co-authorship network of co-authors of Chris G. Antonopoulos
This figure shows the co-authorship network connecting the top 25 collaborators of Chris G. Antonopoulos. A scholar is included among the top collaborators of Chris G. Antonopoulos 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 Chris G. Antonopoulos. Chris G. Antonopoulos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 7 | |
| 5 | 7 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 18 | |
| 10 | 25 | |
| 11 | 24 | |
| 12 | 9 | |
| 13 | 1 | |
| 14 | 9 | |
| 15 | 23 | |
| 16 | 32 | |
| 17 | 3 | |
| 18 | 9 | |
| 19 | 108 | |
| 20 | 20 |
About Chris G. Antonopoulos
Chris G. Antonopoulos is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Aging, having authored 57 papers that have together received 1.2k indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (19 papers), Neural dynamics and brain function (14 papers) and Quantum chaos and dynamical systems (14 papers). The work is most often cited by research in Modeling and Simulation (399 citations), Statistical and Nonlinear Physics (430 citations) and Computer Networks and Communications (296 citations). Chris G. Antonopoulos has collaborated with scholars based in United Kingdom, Greece and Brazil. Frequent co-authors include Argha Mondal, Ian A. Cooper, Tassos Bountis, Ch. Skokos, Murilo S. Baptista, George Papadopoulos, Aggeliki Prayati, Christos Koulamas, Stavros Koubias and Yilun Shang. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.