Shivam Sharma
- Artificial Intelligence top 10%
- Sociology and Political Science
- Information Systems top 10%
- Signal Processing top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Tanmoy ChakrabortyMd Shad AkhtarPreslav NakovAnkush MittalAman SharmaBalasubramanian RamanDimitar DimitrovShraman Pramanick
- Topics
- Speech and Audio Processing (6 papers)Music and Audio Processing (5 papers)Misinformation and Its Impacts (4 papers)
- Journals
- International Journal of Advanced Computer Science and ApplicationsJournal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformationResearch Explorer (The University of Manchester)
In The Last Decade
Shivam Sharma
22 papers receiving 195 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 130
- Sociology and Political Science 107
- Information Systems 73
- Signal Processing 47
- Computer Vision and Pattern Recognition 31
Countries citing papers authored by Shivam Sharma
This map shows the geographic impact of Shivam 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 Shivam Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shivam Sharma more than expected).
Fields of papers citing papers by Shivam Sharma
This network shows the impact of papers produced by Shivam 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 Shivam Sharma. The network helps show where Shivam Sharma may publish in the future.
Co-authorship network of co-authors of Shivam Sharma
This figure shows the co-authorship network connecting the top 25 collaborators of Shivam Sharma. A scholar is included among the top collaborators of Shivam 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 Shivam Sharma. Shivam 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 | 6 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 13 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | 3 | |
| 12 | 58 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 67 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 2 | |
| 19 | 4 | |
| 20 | Speech Recognition with Hidden Markov Model: A Review | 20 |
About Shivam Sharma
Shivam Sharma is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 28 papers that have together received 211 indexed citations. Recurring topics across this work include Speech and Audio Processing (6 papers), Music and Audio Processing (5 papers) and Misinformation and Its Impacts (4 papers). The work is most often cited by research in Signal Processing (47 citations), Artificial Intelligence (130 citations) and Information Systems (73 citations). Shivam Sharma has collaborated with scholars based in India, Qatar and Bulgaria. Frequent co-authors include Tanmoy Chakraborty, Md Shad Akhtar, Preslav Nakov, Ankush Mittal, Aman Sharma, Balasubramanian Raman, Dimitar Dimitrov, Shraman Pramanick, Vinay Kumar Mittal and Avita Katal. Their work appears in journals such as International Journal of Advanced Computer Science and Applications, Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation and Research Explorer (The University of Manchester).
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.