Dilip Kumar Sharma
- Information Systems top 1%
- Artificial Intelligence top 2%
- Sociology and Political Science top 5%
- Molecular Biology
- Signal Processing top 5%
- Co-authors
- Kiran KaliaSonal GargShreya ThakkarRakesh Kumar TekadeVinod TiwariShivani VaidyaRajendra PamulaM. M. Sufyan Beg
- Topics
- Web Data Mining and Analysis (32 papers)Spam and Phishing Detection (28 papers)Misinformation and Its Impacts (23 papers)
- Partner nations
- IndiaUnited StatesSouth Korea
In The Last Decade
Dilip Kumar Sharma
152 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 165
- Information Systems 495
- Artificial Intelligence 482
- Sociology and Political Science 298
- Molecular Biology 240
- Signal Processing 215
Countries citing papers authored by Dilip Kumar Sharma
This map shows the geographic impact of Dilip Kumar 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 Dilip Kumar Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dilip Kumar Sharma more than expected).
Fields of papers citing papers by Dilip Kumar Sharma
This network shows the impact of papers produced by Dilip Kumar 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 Dilip Kumar Sharma. The network helps show where Dilip Kumar Sharma may publish in the future.
Co-authorship network of co-authors of Dilip Kumar Sharma
This figure shows the co-authorship network connecting the top 25 collaborators of Dilip Kumar Sharma. A scholar is included among the top collaborators of Dilip Kumar Sharma based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dilip Kumar Sharma. Dilip Kumar Sharma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 6 | |
| 12 | 6 | |
| 13 | 5 | |
| 14 | 1 | |
| 15 | Hierarchicalrank: webpage rank improvement using HTML taglevel similarity. | 1 |
| 16 | Influence of Deltamethrin and Achook® on Activities of Phosphatases in the Nervous Tissue of Zebrafish, Danio rerio | 1 |
| 17 | Impact of Carbon and Nitrogen Sources on the Trichoderma viride(Biofungicide) and Beauveria bassiana (entomopathogenic fungi) | 8 |
| 18 | Implementation of Secure Cross-site Communication on QIIIEP | 1 |
| 19 | Serum transaminases in prolonged cases of uterine torsion in buffaloes | 2 |
| 20 | 10 |
About Dilip Kumar Sharma
Dilip Kumar Sharma is a scholar working on Signal Processing, Information Systems and Artificial Intelligence, having authored 174 papers that have together received 1.8k indexed citations. Recurring topics across this work include Web Data Mining and Analysis (32 papers), Spam and Phishing Detection (28 papers) and Misinformation and Its Impacts (23 papers). The work is most often cited by research in Information Systems (495 citations), Signal Processing (215 citations) and Artificial Intelligence (482 citations). Dilip Kumar Sharma has collaborated with scholars based in India, United States and South Korea. Frequent co-authors include Kiran Kalia, Sonal Garg, Shreya Thakkar, Rakesh Kumar Tekade, Vinod Tiwari, Shivani Vaidya, Rajendra Pamula, M. M. Sufyan Beg, Shashi Shekhar and Mayank Agrawal. Their work appears in journals such as British Journal of Pharmacology, Acta Biomaterialia and EMBO Reports.
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.