Aritra Dasgupta
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Signal Processing top 10%
- Sociology and Political Science
- Ecological Modeling top 10%
- Co-authors
- Robert KosaraEnrico BertiniMin ChenJorge PocoClaudio SilvaRobert B. CookYaxing WeiJosua Krause
- Topics
- Data Visualization and Analytics (26 papers)Privacy-Preserving Technologies in Data (7 papers)Species Distribution and Climate Change (6 papers)
- Journals
- Atmospheric EnvironmentIEEE Transactions on Visualization and Computer GraphicsComputer Graphics Forum
- Partner nations
- United StatesUnited KingdomNetherlands
In The Last Decade
Aritra Dasgupta
35 papers receiving 581 citations
Peers
Comparison fields: 5 of 85
- Computer Vision and Pattern Recognition 385
- Artificial Intelligence 258
- Signal Processing 84
- Sociology and Political Science 72
- Ecological Modeling 36
Countries citing papers authored by Aritra Dasgupta
This map shows the geographic impact of Aritra Dasgupta'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 Aritra Dasgupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aritra Dasgupta more than expected).
Fields of papers citing papers by Aritra Dasgupta
This network shows the impact of papers produced by Aritra Dasgupta. 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 Aritra Dasgupta. The network helps show where Aritra Dasgupta may publish in the future.
Co-authorship network of co-authors of Aritra Dasgupta
This figure shows the co-authorship network connecting the top 25 collaborators of Aritra Dasgupta. A scholar is included among the top collaborators of Aritra Dasgupta 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 Aritra Dasgupta. Aritra Dasgupta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 27 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 30 | |
| 12 | 23 | |
| 13 | 23 | |
| 14 | Global net land carbon sink: Results from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) | 0 |
| 15 | 20 | |
| 16 | 5 | |
| 17 | 6 | |
| 18 | 37 | |
| 19 | 5 | |
| 20 | 98 |
About Aritra Dasgupta
Aritra Dasgupta is a scholar working on Ecological Modeling, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 40 papers that have together received 606 indexed citations. Recurring topics across this work include Data Visualization and Analytics (26 papers), Privacy-Preserving Technologies in Data (7 papers) and Species Distribution and Climate Change (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (385 citations), Ecological Modeling (36 citations) and Artificial Intelligence (258 citations). Aritra Dasgupta has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Robert Kosara, Enrico Bertini, Min Chen, Jorge Poco, Claudio Silva, Robert B. Cook, Yaxing Wei, Josua Krause, Kyungsik Han and Kristin Cook. Their work appears in journals such as Atmospheric Environment, IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum.
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.