A. Gowrisankar
Impact in
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
- Fractional Differential Equations Solutions
- Mathematical Physics top 5%
- Mathematical Dynamics and Fractals
Papers in
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- Chaos control and synchronization 20
- Advanced Mathematical Theories and Applications 16
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- Mathematical Dynamics and Fractals 30
- Co-authors
- Santo Banerjee (17 shared papers)D. Easwaramoorthy (3 shared papers)Lamberto Rondoni (3 shared papers)R. Uthayakumar (3 shared papers)Asit Saha (5 shared papers)M. G. Prasad (2 shared papers)R. Rakkiyappan (4 shared papers)K. Udhayakumar (3 shared papers)
In The Last Decade
A. Gowrisankar
55 papers receiving 719 citations
Peers
Comparison fields: 5 of 89
- Modeling and Simulation 212
- Mathematical Physics 250
- Statistical and Nonlinear Physics 281
- Economics and Econometrics 135
- Infectious Diseases 83
Countries citing papers authored by A. Gowrisankar
This map shows the geographic impact of A. Gowrisankar'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. Gowrisankar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Gowrisankar more than expected).
Fields of papers citing papers by A. Gowrisankar
This network shows the impact of papers produced by A. Gowrisankar. 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. Gowrisankar. The network helps show where A. Gowrisankar may publish in the future.
Co-authors
The 24 scholars most cited alongside A. Gowrisankar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 76 | |
| 2 | 2020 | 69 | |
| 3 | 2022 | 55 | |
| 4 | 2021 | 47 | |
| 5 | 2021 | 40 | |
| 6 | 2020 | 38 | |
| 7 | 2021 | 31 | |
| 8 | 2020 | 27 | |
| 9 | 2016 | 26 | |
| 10 | 2021 | 26 | |
| 11 | 2021 | 24 | |
| 12 | 2018 | 24 | |
| 13 | 2020 | 23 | |
| 14 | 2022 | 20 | |
| 15 | 2022 | 17 | |
| 16 | 2022 | 12 | |
| 17 | 2020 | 12 | |
| 18 | 2023 | 11 | |
| 19 | 2016 | 10 | |
| 20 | 2024 | 9 |
About A. Gowrisankar
A. Gowrisankar is a scholar working on Statistical and Nonlinear Physics, Mathematical Physics, Economics and Econometrics, Modeling and Simulation and Molecular Biology, having authored 58 papers that have together received 728 indexed citations. Recurring topics across this work include Mathematical Dynamics and Fractals (30 papers), Chaos control and synchronization (20 papers), Complex Systems and Time Series Analysis (19 papers), Advanced Mathematical Theories and Applications (16 papers), Fractional Differential Equations Solutions (12 papers), Fractal and DNA sequence analysis (5 papers), COVID-19 epidemiological studies (3 papers) and Chaos-based Image/Signal Encryption (3 papers). The work is most often cited by research in Modeling and Simulation (212 citations), Mathematical Physics (250 citations), Statistical and Nonlinear Physics (281 citations), Economics and Econometrics (135 citations) and Infectious Diseases (83 citations). A. Gowrisankar has collaborated with scholars based in India, Italy and Malaysia. Frequent co-authors include Santo Banerjee, D. Easwaramoorthy, Lamberto Rondoni, R. Uthayakumar, Asit Saha, M. G. Prasad, R. Rakkiyappan, K. Udhayakumar, Alireza Khalili Golmankhaneh and S. Aasha Nandhini. Their work appears in journals such as The European Physical Journal Special Topics, Fractals, Chaos An Interdisciplinary Journal of Nonlinear Science, Numerical Algorithms and Mathematics and Computers in Simulation.
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.