Asit Kumar Das
Impact in
- Artificial Intelligence top 1%
- Metaheuristic Optimization Algorithms Research
- Topic Modeling
- Advanced Text Analysis Techniques
- Evolutionary Algorithms and Applications
-
- Rough Sets and Fuzzy Logic
Papers in
-
- Text and Document Classification Technologies 20
- Advanced Text Analysis Techniques 16
- Topic Modeling 15
- Evolutionary Algorithms and Applications 12
-
- Data Mining Algorithms and Applications 32
- Co-authors
- Arka Ghosh (12 shared papers)Jaya Sil (8 shared papers)Santanu Phadikar (4 shared papers)Priyanka Das (21 shared papers)Janmenjoy Nayak (19 shared papers)Swagatam Das (8 shared papers)Siddhartha Bhattacharyya (1 shared paper)Soumi Dutta (16 shared papers)
In The Last Decade
Asit Kumar Das
139 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 141
- Artificial Intelligence 1.1k
- Computational Theory and Mathematics 324
- Information Systems 357
- Analytical Chemistry 141
- Computer Vision and Pattern Recognition 259
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 148 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 185 | |
| 2 | 2017 | 139 | |
| 3 | 2018 | 122 | |
| 4 | 2018 | 90 | |
| 5 | 2019 | 63 | |
| 6 | 2018 | 63 | |
| 7 | 2023 | 48 | |
| 8 | 2018 | 46 | |
| 9 | 2019 | 45 | |
| 10 | 2017 | 41 | |
| 11 | 2018 | 39 | |
| 12 | 2022 | 39 | |
| 13 | 2018 | 39 | |
| 14 | 2015 | 38 | |
| 15 | 2017 | 36 | |
| 16 | 2021 | 32 | |
| 17 | 2018 | 32 | |
| 18 | 2019 | 30 | |
| 19 | 2021 | 30 | |
| 20 | 2017 | 28 |
About Asit Kumar Das
Asit Kumar Das is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Statistical and Nonlinear Physics and Molecular Biology, having authored 148 papers that have together received 1.9k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (32 papers), Rough Sets and Fuzzy Logic (27 papers), Complex Network Analysis Techniques (21 papers), Text and Document Classification Technologies (20 papers), Gene expression and cancer classification (16 papers), Advanced Text Analysis Techniques (16 papers), Topic Modeling (15 papers) and Evolutionary Algorithms and Applications (12 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Computational Theory and Mathematics (324 citations), Information Systems (357 citations), Analytical Chemistry (141 citations) and Computer Vision and Pattern Recognition (259 citations). Asit Kumar Das has collaborated with scholars based in India, Italy and China. Frequent co-authors include Arka Ghosh, Jaya Sil, Santanu Phadikar, Priyanka Das, Janmenjoy Nayak, Swagatam Das, Siddhartha Bhattacharyya, Soumi Dutta, Danilo Pelusi and Saptarshi Ghosh. Their work appears in journals such as Applied Soft Computing, Knowledge and Information Systems, IEEE Access, Soft Computing and Multimedia Tools 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.