Munish Kumar
Impact in
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- Hydraulic flow and structures
- Soil and Unsaturated Flow
- Water Systems and Optimization
- Innovative concrete reinforcement materials
- Concrete and Cement Materials Research
- Environmental Engineering top 10%
- Hydrological Forecasting Using AI
Papers in
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- Water Systems and Optimization 5
- Hydraulic flow and structures 5
- Soil and Unsaturated Flow 3
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- Flow Measurement and Analysis 6
- Co-authors
- Parveen Sihag (7 shared papers)Subodh Ranjan (9 shared papers)N. K. Tiwari (9 shared papers)Praveen Jain (1 shared paper)Balraj Singh (1 shared paper)Rakesh Kumar Gupta (1 shared paper)Saad Sh. Sammen (1 shared paper)Anastasia Angelaki (1 shared paper)
In The Last Decade
Munish Kumar
20 papers receiving 346 citations
Peers
Comparison fields: 5 of 45
- Civil and Structural Engineering 234
- Environmental Engineering 103
- Water Science and Technology 98
- Soil Science 45
- Ecology 55
Countries citing papers authored by Munish Kumar
This map shows the geographic impact of Munish 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 Munish Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Munish Kumar more than expected).
Fields of papers citing papers by Munish Kumar
This network shows the impact of papers produced by Munish 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 Munish Kumar. The network helps show where Munish Kumar may publish in the future.
Co-authors
The 15 scholars most cited alongside Munish 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
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 93 | |
| 2 | 2019 | 34 | |
| 3 | 2020 | 31 | |
| 4 | 2020 | 21 | |
| 5 | 2017 | 21 | |
| 6 | 2018 | 21 | |
| 7 | 2018 | 20 | |
| 8 | 2022 | 19 | |
| 9 | 2020 | 16 | |
| 10 | 2021 | 14 | |
| 11 | 2020 | 14 | |
| 12 | 2021 | 10 | |
| 13 | 2021 | 9 | |
| 14 | Enhanced soft computing for ensemble approach to estimate the compressive strength of high strength concrete | 2019 | 6 |
| 15 | 2012 | 6 | |
| 16 | 2023 | 5 | |
| 17 | 2019 | 4 | |
| 18 | 2013 | 3 | |
| 19 | 2022 | 2 | |
| 20 | 2025 | 1 |
About Munish Kumar
Munish Kumar is a scholar working on Civil and Structural Engineering, Mechanics of Materials, Control and Systems Engineering, Aerospace Engineering and Biomedical Engineering, having authored 20 papers that have together received 350 indexed citations. Recurring topics across this work include Flow Measurement and Analysis (6 papers), Water Systems and Optimization (5 papers), Hydraulic flow and structures (5 papers), Fluid Dynamics and Mixing (4 papers), Nuclear Engineering Thermal-Hydraulics (4 papers), Soil and Unsaturated Flow (3 papers), Hydrological Forecasting Using AI (2 papers) and Hydrology and Watershed Management Studies (2 papers). The work is most often cited by research in Civil and Structural Engineering (234 citations), Environmental Engineering (103 citations), Water Science and Technology (98 citations), Soil Science (45 citations) and Ecology (55 citations). Munish Kumar has collaborated with scholars based in India, Nepal and Malaysia. Frequent co-authors include Parveen Sihag, Subodh Ranjan, N. K. Tiwari, Praveen Jain, Balraj Singh, Rakesh Kumar Gupta, Saad Sh. Sammen, Anastasia Angelaki, Siraj Muhammed Pandhiani and Suresh Kumar. Their work appears in journals such as Applied Water Science, Geology Ecology and Landscapes, Water Environment Research, Journal of Environmental Engineering and Modeling Earth Systems and Environment.
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.