Abhimanyu Das
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Statistical and Nonlinear Physics top 5%
- Water Science and Technology top 10%
- Biomedical Engineering
- Co-authors
- David KempeSreenivas GollapudiKamesh MunagalaDavid M. WarsingerDebojyoti DuttaNrisingha DeyIndu B. MaitiRina Panigrahy
- Topics
- Membrane Separation Technologies (7 papers)Complex Network Analysis Techniques (7 papers)Sparse and Compressive Sensing Techniques (6 papers)
- Cited by
- Statistical and Nonlinear PhysicsWater Science and TechnologyComputer Networks and Communications
- Journals
- GeneDesalinationPlanta
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Abhimanyu Das
34 papers receiving 668 citations
Peers
Comparison fields: 5 of 97
- Artificial Intelligence 175
- Computer Networks and Communications 147
- Statistical and Nonlinear Physics 144
- Water Science and Technology 107
- Biomedical Engineering 85
Countries citing papers authored by Abhimanyu Das
This map shows the geographic impact of Abhimanyu Das'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 Abhimanyu Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abhimanyu Das more than expected).
Fields of papers citing papers by Abhimanyu Das
This network shows the impact of papers produced by Abhimanyu Das. 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 Abhimanyu Das. The network helps show where Abhimanyu Das may publish in the future.
Co-authorship network of co-authors of Abhimanyu Das
This figure shows the co-authorship network connecting the top 25 collaborators of Abhimanyu Das. A scholar is included among the top collaborators of Abhimanyu Das 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 Abhimanyu Das. Abhimanyu Das is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 13 | |
| 4 | 16 | |
| 5 | A Convergence Analysis of Gradient Descent on Graph Neural Networks | 1 |
| 6 | 26 | |
| 7 | Approximate submodularity and its applications: subset selection, sparse approximation and dictionary selection | 33 |
| 8 | 26 | |
| 9 | Discovering Topical Aspects in Microblogs | 3 |
| 10 | Effect of Persuasion on Information Diffusion in Social Networks | 1 |
| 11 | 8 | |
| 12 | 22 | |
| 13 | Selecting Diverse Features via Spectral Regularization | 20 |
| 14 | 9 | |
| 15 | 38 | |
| 16 | 6 | |
| 17 | Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection | 52 |
| 18 | 120 | |
| 19 | 23 | |
| 20 | 48 |
About Abhimanyu Das
Abhimanyu Das is a scholar working on Statistical and Nonlinear Physics, Water Science and Technology and Statistics and Probability, having authored 35 papers that have together received 695 indexed citations. Recurring topics across this work include Membrane Separation Technologies (7 papers), Complex Network Analysis Techniques (7 papers) and Sparse and Compressive Sensing Techniques (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (144 citations), Water Science and Technology (107 citations) and Computer Networks and Communications (147 citations). Abhimanyu Das has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include David Kempe, Sreenivas Gollapudi, Kamesh Munagala, David M. Warsinger, Debojyoti Dutta, Nrisingha Dey, Indu B. Maiti, Rina Panigrahy, Mahyar Salek and Amr Ahmed. Their work appears in journals such as Gene, Desalination and Planta.
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.