Asit Kumar Das
Impact in
- Artificial Intelligence top 2%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Topic Modeling
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- Advanced Multi-Objective Optimization Algorithms
- Rough Sets and Fuzzy Logic
Papers in
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- Text and Document Classification Technologies 11
- Evolutionary Algorithms and Applications 9
- Metaheuristic Optimization Algorithms Research 9
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- Data Mining Algorithms and Applications 20
- Co-authors
- Arka Ghosh (11 shared papers)Jaya Sil (4 shared papers)Santanu Phadikar (2 shared papers)Janmenjoy Nayak (19 shared papers)Priyanka Das (14 shared papers)Swagatam Das (8 shared papers)Siddhartha Bhattacharyya (1 shared paper)Danilo Pelusi (14 shared papers)
In The Last Decade
Asit Kumar Das
89 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 132
- Artificial Intelligence 754
- Computational Theory and Mathematics 282
- Computer Vision and Pattern Recognition 216
- Analytical Chemistry 99
- Information Systems 226
Countries citing papers authored by Asit Kumar Das
This map shows the geographic impact of Asit Kumar 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 Asit Kumar Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Asit Kumar Das more than expected).
Fields of papers citing papers by Asit Kumar Das
This network shows the impact of papers produced by Asit Kumar 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 Asit Kumar Das. The network helps show where Asit Kumar Das may publish in the future.
Co-authors
The 25 scholars most cited alongside Asit Kumar Das, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 94 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 162 | |
| 2 | 2017 | 128 | |
| 3 | 2018 | 117 | |
| 4 | 2019 | 62 | |
| 5 | 2018 | 48 | |
| 6 | 2023 | 47 | |
| 7 | 2019 | 44 | |
| 8 | 2017 | 40 | |
| 9 | 2022 | 39 | |
| 10 | 2018 | 39 | |
| 11 | 2017 | 36 | |
| 12 | 2021 | 32 | |
| 13 | 2018 | 32 | |
| 14 | 2019 | 30 | |
| 15 | 2021 | 30 | |
| 16 | 2024 | 25 | |
| 17 | 2015 | 25 | |
| 18 | 2022 | 24 | |
| 19 | 2019 | 24 | |
| 20 | 2017 | 22 |
About Asit Kumar Das
Asit Kumar Das is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 94 papers that have together received 1.4k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (20 papers), Rough Sets and Fuzzy Logic (16 papers), Complex Network Analysis Techniques (12 papers), Text and Document Classification Technologies (11 papers), Evolutionary Algorithms and Applications (9 papers), Metaheuristic Optimization Algorithms Research (9 papers), Face and Expression Recognition (8 papers) and Advanced Multi-Objective Optimization Algorithms (8 papers). The work is most often cited by research in Artificial Intelligence (754 citations), Computational Theory and Mathematics (282 citations), Computer Vision and Pattern Recognition (216 citations), Analytical Chemistry (99 citations) and Information Systems (226 citations). Asit Kumar Das has collaborated with scholars based in India, Italy and China. Frequent co-authors include Arka Ghosh, Jaya Sil, Santanu Phadikar, Janmenjoy Nayak, Priyanka Das, Swagatam Das, Siddhartha Bhattacharyya, Danilo Pelusi, Weiping Ding and Rammohan Mallipeddi. Their work appears in journals such as Applied Soft Computing, IEEE Access, Multimedia Tools and Applications, Knowledge and Information Systems and Neural Computing and Applications.
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.