D. K. Gupta
Impact in
- Numerical Analysis top 2%
- Iterative Methods for Nonlinear Equations
- Advanced Optimization Algorithms Research
- Modeling and Simulation top 2%
- Fractional Differential Equations Solutions
Papers in
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- Iterative Methods for Nonlinear Equations 55
- Advanced Optimization Algorithms Research 47
-
- Matrix Theory and Algorithms 27
- Numerical Methods and Algorithms 9
- Co-authors
- Sukhjit Singh (18 shared papers)Eulalia Martı́nez (13 shared papers)José L. Hueso (8 shared papers)M. Prashanth (10 shared papers)Predrag S. Stanimirović (6 shared papers)Adrijit Goswami (1 shared paper)Gour Chandra Mahata (1 shared paper)Ramandeep Behl (1 shared paper)
In The Last Decade
D. K. Gupta
72 papers receiving 398 citations
Peers
Comparison fields: 5 of 51
- Numerical Analysis 314
- Modeling and Simulation 156
- Computational Theory and Mathematics 174
- Mathematical Physics 43
- Management Information Systems 23
Countries citing papers authored by D. K. Gupta
This map shows the geographic impact of D. K. Gupta'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 D. K. Gupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. K. Gupta more than expected).
Fields of papers citing papers by D. K. Gupta
This network shows the impact of papers produced by D. K. Gupta. 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 D. K. Gupta. The network helps show where D. K. Gupta may publish in the future.
Co-authors
The 25 scholars most cited alongside D. K. Gupta, 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 79 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 54 | |
| 2 | 2016 | 27 | |
| 3 | 2005 | 24 | |
| 4 | 2017 | 21 | |
| 5 | 2008 | 19 | |
| 6 | 2010 | 17 | |
| 7 | 2017 | 15 | |
| 8 | 2016 | 15 | |
| 9 | 2010 | 15 | |
| 10 | 2016 | 12 | |
| 11 | 2016 | 11 | |
| 12 | 2013 | 9 | |
| 13 | 2014 | 8 | |
| 14 | 2005 | 8 | |
| 15 | 2017 | 7 | |
| 16 | 2010 | 7 | |
| 17 | 2013 | 6 | |
| 18 | 2019 | 6 | |
| 19 | 2010 | 6 | |
| 20 | 2015 | 6 |
About D. K. Gupta
D. K. Gupta is a scholar working on Numerical Analysis, Computational Theory and Mathematics, Modeling and Simulation, Artificial Intelligence and Signal Processing, having authored 79 papers that have together received 427 indexed citations. Recurring topics across this work include Iterative Methods for Nonlinear Equations (55 papers), Advanced Optimization Algorithms Research (47 papers), Fractional Differential Equations Solutions (31 papers), Matrix Theory and Algorithms (27 papers), Numerical Methods and Algorithms (9 papers), Numerical methods in inverse problems (6 papers), Data Management and Algorithms (4 papers) and Coding theory and cryptography (4 papers). The work is most often cited by research in Numerical Analysis (314 citations), Modeling and Simulation (156 citations), Computational Theory and Mathematics (174 citations), Mathematical Physics (43 citations) and Management Information Systems (23 citations). D. K. Gupta has collaborated with scholars based in India, Spain and Serbia. Frequent co-authors include Sukhjit Singh, Eulalia Martı́nez, José L. Hueso, M. Prashanth, Predrag S. Stanimirović, Adrijit Goswami, Gour Chandra Mahata, Ramandeep Behl, S. S. Motsa and Chaitanya Kaul. Their work appears in journals such as Applied Mathematics and Computation, Journal of Computational and Applied Mathematics, International Journal of Computational Methods, Sadhana and CALCOLO.
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.