Prashant Singh

29 papers receiving 466 citations

Peers

Prashant Singh
Comparison fields: 5 of 81
  • Statistics, Probability and Uncertainty 41
  • Computational Theory and Mathematics 85
  • Plant Science 171
  • Management Science and Operations Research 38
  • Computational Mechanics 58
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Robert G. Hardin United States
Xiaodong Cheng Netherlands
Rasmus K. Ursem Denmark
Vítor V. Lopes Portugal
Rajashree Mishra India
Susanta Dutta India
Dries Telen Belgium
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Citations per field
00.5×6.8×
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Citations per year

Countries citing papers authored by Prashant Singh

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Prashant Singh Line = papers co-authored together Prashant Singh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014101
2 201387
3 201557
4 201730
5 202229
6 201424
7 201716
8 201614
9 201313
10 201312
11 202211
12 201111
13 201611
14 201311
15 20169
16 20138
17 20215
18 20205
19 20244
20 20244

About Prashant Singh

Prashant Singh is a scholar working on Computational Theory and Mathematics, Electrical and Electronic Engineering, Molecular Biology, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 33 papers that have together received 481 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (8 papers), Probabilistic and Robust Engineering Design (6 papers), Optimal Experimental Design Methods (5 papers), Gene Regulatory Network Analysis (4 papers), Markov Chains and Monte Carlo Methods (3 papers), Electromagnetic Compatibility and Noise Suppression (3 papers), Electromagnetic Compatibility and Measurements (3 papers) and Cyclone Separators and Fluid Dynamics (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (41 citations), Computational Theory and Mathematics (85 citations), Plant Science (171 citations), Management Science and Operations Research (38 citations) and Computational Mechanics (58 citations). Prashant Singh has collaborated with scholars based in Sweden, Belgium and India. Frequent co-authors include Vinod Kumar, Sanjeev Agrawal, Tom Dhaene, Dirk Deschrijver, Ivo Couckuyt, Khairy Elsayed, Milko A. Jorquera, Ashok Kumar Verma, Punesh Sangwan and Piyush Kumar. Their work appears in journals such as PLoS Computational Biology, Bioinformatics, IEEE Transactions on Electromagnetic Compatibility, Journal of Optimization Theory and Applications and Research Journal of Medicinal Plant.

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.

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