Anirvan M. Sengupta
About
In The Last Decade
Anirvan M. Sengupta
189 papers receiving 3.7k citations
Peers
Comparison fields: 5 of 149
- Molecular Biology 1.3k
- Electrical and Electronic Engineering 834
- Nuclear and High Energy Physics 481
- Atomic and Molecular Physics, and Optics 461
- Condensed Matter Physics 449
Countries citing papers authored by Anirvan M. Sengupta
This map shows the geographic impact of Anirvan M. Sengupta'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 Anirvan M. Sengupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anirvan M. Sengupta more than expected).
Fields of papers citing papers by Anirvan M. Sengupta
This network shows the impact of papers produced by Anirvan M. Sengupta. 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 Anirvan M. Sengupta. The network helps show where Anirvan M. Sengupta may publish in the future.
Co-authorship network of co-authors of Anirvan M. Sengupta
This figure shows the co-authorship network connecting the top 25 collaborators of Anirvan M. Sengupta. A scholar is included among the top collaborators of Anirvan M. Sengupta 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 Anirvan M. Sengupta. Anirvan M. Sengupta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 19 | |
| 3 | 1 | |
| 4 | A simple normative network approximates local non-Hebbian learning in the cortex | 1 |
| 5 | A Similarity-preserving Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit | 3 |
| 6 | 2 | |
| 7 | Clustering is semidefinitely not that hard: Nonnegative SDP for manifold disentangling | 2 |
| 8 | 1 | |
| 9 | 16 | |
| 10 | 0 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 73 | |
| 14 | 32 | |
| 15 | 63 | |
| 16 | 15 | |
| 17 | 14 | |
| 18 | 10 | |
| 19 | 160 | |
| 20 | A new approach to relief valve load calculations. | 3 |
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.