Prashant Singh
Impact in
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- Probabilistic and Robust Engineering Design
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- Advanced Multi-Objective Optimization Algorithms
Papers in
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- Gene Regulatory Network Analysis 6
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- Gaussian Processes and Bayesian Inference 3
- Co-authors
- Sanjeev Agrawal (2 shared papers)Vinod Kumar (2 shared papers)Tom Dhaene (12 shared papers)Dirk Deschrijver (11 shared papers)Ivo Couckuyt (7 shared papers)Khairy Elsayed (2 shared papers)Milko A. Jorquera (1 shared paper)Piyush Kumar (1 shared paper)
In The Last Decade
Prashant Singh
29 papers receiving 455 citations
Peers
Comparison fields: 5 of 81
- Statistics, Probability and Uncertainty 41
- Computational Theory and Mathematics 82
- Plant Science 172
- Management Science and Operations Research 38
- Computational Mechanics 55
Countries citing papers authored by Prashant Singh
This map shows the geographic impact of Prashant Singh'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 Prashant Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prashant Singh more than expected).
Fields of papers citing papers by Prashant Singh
This network shows the impact of papers produced by Prashant Singh. 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 Prashant Singh. The network helps show where Prashant Singh may publish in the future.
Co-authors
The 25 scholars most cited alongside Prashant Singh, 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 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 100 | |
| 2 | 2013 | 87 | |
| 3 | 2015 | 55 | |
| 4 | 2017 | 28 | |
| 5 | 2022 | 27 | |
| 6 | 2014 | 24 | |
| 7 | 2016 | 14 | |
| 8 | 2017 | 14 | |
| 9 | 2013 | 12 | |
| 10 | 2013 | 12 | |
| 11 | 2022 | 11 | |
| 12 | 2013 | 11 | |
| 13 | 2011 | 11 | |
| 14 | 2016 | 11 | |
| 15 | 2016 | 9 | |
| 16 | 2013 | 8 | |
| 17 | 2021 | 5 | |
| 18 | 2020 | 5 | |
| 19 | 2024 | 4 | |
| 20 | 2014 | 4 |
About Prashant Singh
Prashant Singh is a scholar working on Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Electrical and Electronic Engineering and Statistics, Probability and Uncertainty, having authored 34 papers that have together received 470 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (8 papers), Probabilistic and Robust Engineering Design (7 papers), Gene Regulatory Network Analysis (6 papers), Optimal Experimental Design Methods (5 papers), Gaussian Processes and Bayesian Inference (3 papers), Markov Chains and Monte Carlo Methods (3 papers), Electromagnetic Compatibility and Measurements (3 papers) and Electromagnetic Compatibility and Noise Suppression (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (41 citations), Computational Theory and Mathematics (82 citations), Plant Science (172 citations), Management Science and Operations Research (38 citations) and Computational Mechanics (55 citations). Prashant Singh has collaborated with scholars based in Sweden, Belgium and India. Frequent co-authors include Sanjeev Agrawal, Vinod Kumar, Tom Dhaene, Dirk Deschrijver, Ivo Couckuyt, Khairy Elsayed, Milko A. Jorquera, Piyush Kumar, Ashok Kumar Verma and Punesh Sangwan. Their work appears in journals such as PLoS Computational Biology, Bioinformatics, IEEE Transactions on Electromagnetic Compatibility, Structural and Multidisciplinary Optimization and BMC Bioinformatics.
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.