Arvind Yadav
Impact in
- Water Science and Technology top 10%
- Hydrology and Watershed Management Studies
- Environmental Engineering top 10%
- Hydrological Forecasting Using AI
Papers in
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- Hydrological Forecasting Using AI 12
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- Hydrology and Watershed Management Studies 11
- Co-authors
- Sk. Md. Equeenuddin (3 shared papers)Snehamoy Chatterjee (3 shared papers)Devendra Joshi (11 shared papers)Hitesh Mohapatra (3 shared papers)Chadi Altrjman (1 shared paper)Bhabendu Kumar Mohanta (1 shared paper)Fadi Al‐Turjman (1 shared paper)Premkumar Chithaluru (8 shared papers)
- Journals
- Water (5 papers)Hydrological Sciences Journal (1 paper)Scientific Reports (1 paper)Electronics (1 paper)Applied Sciences (1 paper)
- Partner nations
- IndiaSaudi ArabiaMexico
In The Last Decade
Arvind Yadav
25 papers receiving 293 citations
Peers
Comparison fields: 5 of 78
- Water Science and Technology 114
- Environmental Engineering 113
- Information Systems 60
- Computer Networks and Communications 59
- Ecology 63
Countries citing papers authored by Arvind Yadav
This map shows the geographic impact of Arvind Yadav'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 Arvind Yadav with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arvind Yadav more than expected).
Fields of papers citing papers by Arvind Yadav
This network shows the impact of papers produced by Arvind Yadav. 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 Arvind Yadav. The network helps show where Arvind Yadav may publish in the future.
Co-authors
The 25 scholars most cited alongside Arvind Yadav, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 51 | |
| 2 | 2018 | 33 | |
| 3 | 2020 | 29 | |
| 4 | 2017 | 26 | |
| 5 | 2019 | 24 | |
| 6 | 2020 | 23 | |
| 7 | 2011 | 18 | |
| 8 | 2022 | 18 | |
| 9 | 2022 | 16 | |
| 10 | 2022 | 14 | |
| 11 | 2023 | 10 | |
| 12 | 2022 | 9 | |
| 13 | 2022 | 8 | |
| 14 | 2020 | 8 | |
| 15 | 2022 | 8 | |
| 16 | 2020 | 6 | |
| 17 | 2022 | 5 | |
| 18 | 2022 | 5 | |
| 19 | 2023 | 5 | |
| 20 | 2024 | 4 |
About Arvind Yadav
Arvind Yadav is a scholar working on Environmental Engineering, Water Science and Technology, Ecology, Control and Systems Engineering and Mechanical Engineering, having authored 26 papers that have together received 328 indexed citations. Recurring topics across this work include Hydrological Forecasting Using AI (12 papers), Hydrology and Watershed Management Studies (11 papers), Hydrology and Sediment Transport Processes (10 papers), Mining Techniques and Economics (4 papers), Belt Conveyor Systems Engineering (4 papers), Mineral Processing and Grinding (4 papers), COVID-19 diagnosis using AI (2 papers) and Pharmacological Effects and Toxicity Studies (1 paper). The work is most often cited by research in Water Science and Technology (114 citations), Environmental Engineering (113 citations), Information Systems (60 citations), Computer Networks and Communications (59 citations) and Ecology (63 citations). Arvind Yadav has collaborated with scholars based in India, Saudi Arabia and Mexico. Frequent co-authors include Sk. Md. Equeenuddin, Snehamoy Chatterjee, Devendra Joshi, Hitesh Mohapatra, Chadi Altrjman, Bhabendu Kumar Mohanta, Fadi Al‐Turjman, Premkumar Chithaluru, Aman Singh and Vinod Kumar. Their work appears in journals such as Water, Hydrological Sciences Journal, Scientific Reports, Electronics and Applied Sciences.
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.