Vikas Solanki
Impact in
- Health Information Management top 10%
- Artificial Intelligence in Healthcare
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- Smart Agriculture and AI
- Plant Virus Research Studies
- Plant Disease Management Techniques
- Plant Pathogenic Bacteria Studies
Papers in
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- Plant Virus Research Studies 7
- Plant Pathogenic Bacteria Studies 4
- Smart Agriculture and AI 4
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- Anomaly Detection Techniques and Applications 2
- Co-authors
- Vinay Kukreja (4 shared papers)Ravi Kumar Sachdeva (5 shared papers)Deepak Kumar (1 shared paper)Ankit Bansal (2 shared papers)Amanpreet Kaur (1 shared paper)Rishabh Sharma (1 shared paper)Rakesh Ahuja (4 shared papers)Bikash Mandal (5 shared papers)
In The Last Decade
Vikas Solanki
22 papers receiving 232 citations
Peers
Comparison fields: 5 of 89
- Health Information Management 24
- Plant Science 94
- Computer Vision and Pattern Recognition 39
- Management Science and Operations Research 17
- Analytical Chemistry 13
Countries citing papers authored by Vikas Solanki
This map shows the geographic impact of Vikas Solanki'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 Vikas Solanki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vikas Solanki more than expected).
Fields of papers citing papers by Vikas Solanki
This network shows the impact of papers produced by Vikas Solanki. 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 Vikas Solanki. The network helps show where Vikas Solanki may publish in the future.
Co-authors
The 25 scholars most cited alongside Vikas Solanki, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 58 | |
| 2 | 2022 | 51 | |
| 3 | 2023 | 26 | |
| 4 | 2022 | 19 | |
| 5 | 2017 | 11 | |
| 6 | 2021 | 11 | |
| 7 | 2023 | 8 | |
| 8 | 2023 | 8 | |
| 9 | 2022 | 7 | |
| 10 | 2020 | 6 | |
| 11 | 2021 | 6 | |
| 12 | 2020 | 5 | |
| 13 | 2022 | 5 | |
| 14 | 2022 | 5 | |
| 15 | 2015 | 4 | |
| 16 | 2022 | 4 | |
| 17 | 2022 | 4 | |
| 18 | 2022 | 3 | |
| 19 | 2021 | 3 | |
| 20 | 2023 | 1 |
About Vikas Solanki
Vikas Solanki is a scholar working on Plant Science, Artificial Intelligence, Computer Networks and Communications, Molecular Biology and Health Information Management, having authored 27 papers that have together received 247 indexed citations. Recurring topics across this work include Plant Virus Research Studies (7 papers), Plant Pathogenic Bacteria Studies (4 papers), Smart Agriculture and AI (4 papers), Forecasting Techniques and Applications (3 papers), Stock Market Forecasting Methods (3 papers), Artificial Intelligence in Healthcare (3 papers), Plant Pathogens and Fungal Diseases (2 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Health Information Management (24 citations), Plant Science (94 citations), Computer Vision and Pattern Recognition (39 citations), Management Science and Operations Research (17 citations) and Analytical Chemistry (13 citations). Vikas Solanki has collaborated with scholars based in India, Nepal and Oman. Frequent co-authors include Vinay Kukreja, Ravi Kumar Sachdeva, Deepak Kumar, Ankit Bansal, Amanpreet Kaur, Rishabh Sharma, Rakesh Ahuja, Bikash Mandal, Pooja Rani and Sunil Gupta. Their work appears in journals such as Virus Research, Virus Genes, Plants, Frontiers in Microbiology and Journal of Failure Analysis and Prevention.
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.