Argha Mondal
- Modeling and Simulation top 0.5%
- Statistical and Nonlinear Physics top 2%
- Cognitive Neuroscience top 10%
- Computer Networks and Communications top 5%
- Public Health, Environmental and Occupational Health top 10%
- Co-authors
- Chris G. AntonopoulosIan A. CooperRanjit Kumar UpadhyayWondimu TekaJun MaM. A. Aziz-AlaouiChittaranjan HensÉva Kaslik
- Topics
- stochastic dynamics and bifurcation (28 papers)Neural dynamics and brain function (25 papers)Nonlinear Dynamics and Pattern Formation (22 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsNeural Networks
- Partner nations
- IndiaUnited KingdomUnited States
In The Last Decade
Argha Mondal
33 papers receiving 916 citations
Peers
Comparison fields: 5 of 100
- Modeling and Simulation 455
- Statistical and Nonlinear Physics 404
- Cognitive Neuroscience 235
- Computer Networks and Communications 233
- Public Health, Environmental and Occupational Health 170
Countries citing papers authored by Argha Mondal
This map shows the geographic impact of Argha Mondal'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 Argha Mondal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Argha Mondal more than expected).
Fields of papers citing papers by Argha Mondal
This network shows the impact of papers produced by Argha Mondal. 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 Argha Mondal. The network helps show where Argha Mondal may publish in the future.
Co-authorship network of co-authors of Argha Mondal
This figure shows the co-authorship network connecting the top 25 collaborators of Argha Mondal. A scholar is included among the top collaborators of Argha Mondal 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 Argha Mondal. Argha Mondal 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 | 3 | |
| 3 | 7 | |
| 4 | 8 | |
| 5 | 4 | |
| 6 | 10 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 8 | |
| 11 | 4 | |
| 12 | 8 | |
| 13 | 483 | |
| 14 | 57 | |
| 15 | 74 | |
| 16 | 13 | |
| 17 | 2 | |
| 18 | 40 | |
| 19 | 2 | |
| 20 | Dynamics of fractional order modified Morris-Lecar neural model | 10 |
About Argha Mondal
Argha Mondal is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Modeling and Simulation, having authored 34 papers that have together received 943 indexed citations. Recurring topics across this work include stochastic dynamics and bifurcation (28 papers), Neural dynamics and brain function (25 papers) and Nonlinear Dynamics and Pattern Formation (22 papers). The work is most often cited by research in Modeling and Simulation (455 citations), Statistical and Nonlinear Physics (404 citations) and Cognitive Neuroscience (235 citations). Argha Mondal has collaborated with scholars based in India, United Kingdom and United States. Frequent co-authors include Chris G. Antonopoulos, Ian A. Cooper, Ranjit Kumar Upadhyay, Wondimu Teka, Jun Ma, M. A. Aziz-Alaoui, Chittaranjan Hens, Éva Kaslik, Swarup Poria and Mohammad Ali Khan. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Neural Networks.
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.