A. M. Albano
- Statistical and Nonlinear Physics top 0.5%
- Cognitive Neuroscience top 2%
- Economics and Econometrics top 2%
- Computer Networks and Communications top 2%
- Artificial Intelligence top 5%
- Co-authors
- Paul E. RappDick BedeauxChristopher J. CellucciA.I. MeesI. D. ZimmermanP. MazurC.A. SchwartzA. Passamante
- Topics
- Chaos control and synchronization (18 papers)Complex Systems and Time Series Analysis (11 papers)Nonlinear Dynamics and Pattern Formation (9 papers)
- Journals
- Proceedings of the National Academy of SciencesPhysical review. B, Condensed matterPhysical Review A
- Partner nations
- United StatesNetherlandsPhilippines
In The Last Decade
A. M. Albano
54 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 136
- Statistical and Nonlinear Physics 1.2k
- Cognitive Neuroscience 792
- Economics and Econometrics 604
- Computer Networks and Communications 467
- Artificial Intelligence 310
Countries citing papers authored by A. M. Albano
This map shows the geographic impact of A. M. Albano'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 A. M. Albano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. M. Albano more than expected).
Fields of papers citing papers by A. M. Albano
This network shows the impact of papers produced by A. M. Albano. 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 A. M. Albano. The network helps show where A. M. Albano may publish in the future.
Co-authorship network of co-authors of A. M. Albano
This figure shows the co-authorship network connecting the top 25 collaborators of A. M. Albano. A scholar is included among the top collaborators of A. M. Albano 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 A. M. Albano. A. M. Albano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 111 | |
| 2 | 67 | |
| 3 | 16 | |
| 4 | 16 | |
| 5 | 6 | |
| 6 | 10 | |
| 7 | 131 | |
| 8 | 0 | |
| 9 | 90 | |
| 10 | 29 | |
| 11 | 5 | |
| 12 | 29 | |
| 13 | Filtered Noise Can Mimic Low-Dimensional Chaotic Attractors | 1 |
| 14 | 63 | |
| 15 | 209 | |
| 16 | 7 | |
| 17 | 2 | |
| 18 | Measurements of instabilities and chaos in single-mode inhomogeneously broadened lasers (A) | 1 |
| 19 | 12 | |
| 20 | 1 |
About A. M. Albano
A. M. Albano is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Signal Processing, having authored 58 papers that have together received 2.6k indexed citations. Recurring topics across this work include Chaos control and synchronization (18 papers), Complex Systems and Time Series Analysis (11 papers) and Nonlinear Dynamics and Pattern Formation (9 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.2k citations), Cognitive Neuroscience (792 citations) and Economics and Econometrics (604 citations). A. M. Albano has collaborated with scholars based in United States, Netherlands and Philippines. Frequent co-authors include Paul E. Rapp, Dick Bedeaux, Christopher J. Cellucci, A.I. Mees, I. D. Zimmerman, P. Mazur, C.A. Schwartz, A. Passamante, Tanya Schmah and Jacques Martinerie. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical review. B, Condensed matter and Physical Review 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.