Asim Kumer Dey
- Statistical and Nonlinear Physics top 10%
- Economics and Econometrics
- Artificial Intelligence
- Molecular Biology
- Global and Planetary Change
- Co-authors
- Yulia R. GelH. Vincent PoorVyacheslav LyubchichMurat KantarcıoğluCüneyt Gürcan AkçoraIrina PanovskaStephen J. YoungJie Zhang
- Topics
- Complex Network Analysis Techniques (8 papers)Topological and Geometric Data Analysis (4 papers)Hydrology and Drought Analysis (3 papers)
- Journals
- Proceedings of the National Academy of SciencesPhysica A Statistical Mechanics and its ApplicationsJournal of the Royal Statistical Society Series A (Statistics in Society)
- Partner nations
- United StatesBangladeshJapan
In The Last Decade
Asim Kumer Dey
15 papers receiving 235 citations
Peers
Comparison fields: 5 of 76
- Statistical and Nonlinear Physics 83
- Economics and Econometrics 57
- Artificial Intelligence 33
- Molecular Biology 27
- Global and Planetary Change 22
Countries citing papers authored by Asim Kumer Dey
This map shows the geographic impact of Asim Kumer Dey'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 Asim Kumer Dey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Asim Kumer Dey more than expected).
Fields of papers citing papers by Asim Kumer Dey
This network shows the impact of papers produced by Asim Kumer Dey. 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 Asim Kumer Dey. The network helps show where Asim Kumer Dey may publish in the future.
Co-authorship network of co-authors of Asim Kumer Dey
This figure shows the co-authorship network connecting the top 25 collaborators of Asim Kumer Dey. A scholar is included among the top collaborators of Asim Kumer Dey 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 Asim Kumer Dey. Asim Kumer Dey 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 | 0 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 33 | |
| 7 | 13 | |
| 8 | 18 | |
| 9 | 15 | |
| 10 | 82 | |
| 11 | 18 | |
| 12 | 4 | |
| 13 | 8 | |
| 14 | 4 | |
| 15 | 23 | |
| 16 | Regression Analysis for Data Containing Outliers and High Leverage Points | 4 |
| 17 | 12 |
About Asim Kumer Dey
Asim Kumer Dey is a scholar working on Statistical and Nonlinear Physics, Computational Theory and Mathematics and General Economics, Econometrics and Finance, having authored 17 papers that have together received 243 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (8 papers), Topological and Geometric Data Analysis (4 papers) and Hydrology and Drought Analysis (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (83 citations), Economics and Econometrics (57 citations) and Modeling and Simulation (8 citations). Asim Kumer Dey has collaborated with scholars based in United States, Bangladesh and Japan. Frequent co-authors include Yulia R. Gel, H. Vincent Poor, Vyacheslav Lyubchich, Murat Kantarcıoğlu, Cüneyt Gürcan Akçora, Irina Panovska, Stephen J. Young, Jie Zhang, Binghui Li and Abhijit Mandal. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physica A Statistical Mechanics and its Applications and Journal of the Royal Statistical Society Series A (Statistics in Society).
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.