Jai Kumar
Impact in
- Computational Mechanics top 5%
- Fluid Dynamics and Turbulent Flows
- Heat and Mass Transfer in Porous Media
- Lattice Boltzmann Simulation Studies
- Fluid Dynamics and Thin Films
- Modeling and Simulation top 10%
Papers in
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- Fluid Dynamics and Turbulent Flows 10
- Fluid Dynamics and Thin Films 10
- Lattice Boltzmann Simulation Studies 8
- Heat and Mass Transfer in Porous Media 8
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- Nanofluid Flow and Heat Transfer 20
- Co-authors
- B. M. Shankar (17 shared papers)I. S. Shivakumara (15 shared papers)Vineet K. Srivastava (10 shared papers)P. Bera (4 shared papers)Badam Singh Kushvah (8 shared papers)Arzhang Khalili (2 shared papers)H. S. Shukla (2 shared papers)Mohammad Tamsir (2 shared papers)
In The Last Decade
Jai Kumar
39 papers receiving 498 citations
Peers
Comparison fields: 5 of 61
- Computational Mechanics 330
- Modeling and Simulation 38
- Fluid Flow and Transfer Processes 47
- Numerical Analysis 37
- Biomedical Engineering 294
Countries citing papers authored by Jai Kumar
This map shows the geographic impact of Jai Kumar'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 Jai Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jai Kumar more than expected).
Fields of papers citing papers by Jai Kumar
This network shows the impact of papers produced by Jai Kumar. 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 Jai Kumar. The network helps show where Jai Kumar may publish in the future.
Co-authors
The 24 scholars most cited alongside Jai Kumar, 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 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 60 | |
| 2 | 2014 | 41 | |
| 3 | 2014 | 33 | |
| 4 | 2021 | 27 | |
| 5 | 2010 | 27 | |
| 6 | 2011 | 22 | |
| 7 | 2016 | 21 | |
| 8 | 2014 | 21 | |
| 9 | 2016 | 20 | |
| 10 | 2019 | 19 | |
| 11 | 2020 | 16 | |
| 12 | 2014 | 16 | |
| 13 | 2020 | 15 | |
| 14 | 2016 | 15 | |
| 15 | 2019 | 14 | |
| 16 | 2015 | 13 | |
| 17 | 2011 | 12 | |
| 18 | 2017 | 11 | |
| 19 | 2017 | 10 | |
| 20 | 2015 | 10 |
About Jai Kumar
Jai Kumar is a scholar working on Computational Mechanics, Biomedical Engineering, Astronomy and Astrophysics, Aerospace Engineering and Oceanography, having authored 40 papers that have together received 518 indexed citations. Recurring topics across this work include Nanofluid Flow and Heat Transfer (20 papers), Fluid Dynamics and Turbulent Flows (10 papers), Fluid Dynamics and Thin Films (10 papers), Lattice Boltzmann Simulation Studies (8 papers), Heat and Mass Transfer in Porous Media (8 papers), Spacecraft Dynamics and Control (5 papers), Astro and Planetary Science (4 papers) and Power Transformer Diagnostics and Insulation (3 papers). The work is most often cited by research in Computational Mechanics (330 citations), Modeling and Simulation (38 citations), Fluid Flow and Transfer Processes (47 citations), Numerical Analysis (37 citations) and Biomedical Engineering (294 citations). Jai Kumar has collaborated with scholars based in India, Germany and Indonesia. Frequent co-authors include B. M. Shankar, I. S. Shivakumara, Vineet K. Srivastava, P. Bera, Badam Singh Kushvah, Arzhang Khalili, H. S. Shukla, Mohammad Tamsir, I. S. Shivakumara and Ashok Kumar. Their work appears in journals such as Acta Astronautica, Acta Mechanica, International Journal of Heat and Mass Transfer, Physics of Fluids and Applied Mathematics and Computation.
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.