Sanjiv Sharma
- Neurology top 10%
- Environmental Engineering top 10%
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- Mobile Ad Hoc Networks 5
- Opportunistic and Delay-Tolerant Networks 5
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- Imbalanced Data Classification Techniques 6
- Sentiment Analysis and Opinion Mining 3
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- Data Mining Algorithms and Applications 5
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- Vehicular Ad Hoc Networks (VANETs) 5
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- Big Data and Business Intelligence 3
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- Time Series Analysis and Forecasting 3
- Co-authors
- Neelam MishraAndrew NicolaidesJasjit S. SuriJaume Roquer GonzálezMercedes BalcellsHarman S. SuriNarendra N. KhannaMonika Turk
- Cited by
- NeurologyEnvironmental Engineering
- Journals
- SHILAP Revista de lepidopterología (1 paper)Materials Today Proceedings (4 papers)Journal of Stroke (1 paper)
- Partner nations
- IndiaUnited Arab EmiratesCyprus
In The Last Decade
Sanjiv Sharma
29 papers receiving 401 citations
Peers
Comparison fields: 5 of 96
- Neurology 76
- Environmental Engineering 79
- Neurology 83
- Computer Networks and Communications 69
- Management Science and Operations Research 34
Countries citing papers authored by Sanjiv Sharma
This map shows the geographic impact of Sanjiv Sharma'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 Sanjiv Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanjiv Sharma more than expected).
Fields of papers citing papers by Sanjiv Sharma
This network shows the impact of papers produced by Sanjiv Sharma. 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 Sanjiv Sharma. The network helps show where Sanjiv Sharma may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Sanjiv Sharma, 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 | 2023 | 1 | |
| 2 | 2023 | 3 | |
| 3 | 2023 | 1 | |
| 4 | 2022 | 3 | |
| 5 | 2020 | 2 | |
| 6 | 2020 | 1 | |
| 7 | 2019 | 0 | |
| 8 | 2018 | 3 | |
| 9 | 2018 | 203 | |
| 10 | 2018 | 85 | |
| 11 | 2018 | 1 | |
| 12 | 2018 | 1 | |
| 13 | 2017 | 1 | |
| 14 | 2017 | 40 | |
| 15 | 2016 | 3 | |
| 16 | 2016 | 8 | |
| 17 | 2015 | 1 | |
| 18 | Analysis & modeling multi-breeded Mean-Minded ant colony optimization of agent based Road Vehicle Routing Management | 2012 | 8 |
| 19 | 2012 | 3 | |
| 20 | Improved BSP Clustering Algorithm For Social Network Analysis | 2010 | 3 |
About Sanjiv Sharma
Sanjiv Sharma is a scholar working on Health Informatics, Artificial Intelligence and Health Information Management, having authored 33 papers that have together received 459 indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (6 papers), Data Mining Algorithms and Applications (5 papers), Mobile Ad Hoc Networks (5 papers), Opportunistic and Delay-Tolerant Networks (5 papers), Vehicular Ad Hoc Networks (VANETs) (5 papers), Big Data and Business Intelligence (3 papers), Sentiment Analysis and Opinion Mining (3 papers) and Time Series Analysis and Forecasting (3 papers). The work is most often cited by research in Neurology (76 citations), Environmental Engineering (79 citations) and Neurology (83 citations). Sanjiv Sharma has collaborated with scholars based in India, United Arab Emirates and Cyprus. Frequent co-authors include Neelam Mishra, Andrew Nicolaides, Jasjit S. Suri, Jaume Roquer González, Mercedes Balcells, Harman S. Suri, Narendra N. Khanna, Monika Turk, Luca Saba and Ángel Ois. Their work appears in journals such as SHILAP Revista de lepidopterología, Materials Today Proceedings and Journal of Stroke.
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.