Shraman Pramanick
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Sociology and Political Science
- Social Psychology
- Information Systems
- Co-authors
- Md Shad AkhtarTanmoy ChakrabortyShivam SharmaPreslav NakovDimitar DimitrovPengchuan ZhangKevin Qinghong LinMike Zheng Shou
- Topics
- Sentiment Analysis and Opinion Mining (4 papers)EEG and Brain-Computer Interfaces (3 papers)Misinformation and Its Impacts (3 papers)
- Journals
- Biomedical Signal Processing and ControlarXiv (Cornell University)2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
- Partner nations
- IndiaUnited StatesSingapore
In The Last Decade
Shraman Pramanick
10 papers receiving 173 citations
Peers
Comparison fields: 5 of 42
- Artificial Intelligence 111
- Computer Vision and Pattern Recognition 71
- Sociology and Political Science 38
- Social Psychology 28
- Information Systems 18
Countries citing papers authored by Shraman Pramanick
This map shows the geographic impact of Shraman Pramanick'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 Shraman Pramanick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shraman Pramanick more than expected).
Fields of papers citing papers by Shraman Pramanick
This network shows the impact of papers produced by Shraman Pramanick. 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 Shraman Pramanick. The network helps show where Shraman Pramanick may publish in the future.
Co-authorship network of co-authors of Shraman Pramanick
This figure shows the co-authorship network connecting the top 25 collaborators of Shraman Pramanick. A scholar is included among the top collaborators of Shraman Pramanick 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 Shraman Pramanick. Shraman Pramanick is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 32 | |
| 5 | 25 | |
| 6 | 40 | |
| 7 | 58 | |
| 8 | 2 | |
| 9 | 11 | |
| 10 | 1 | |
| 11 | 0 |
About Shraman Pramanick
Shraman Pramanick is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Social Psychology, having authored 11 papers that have together received 179 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (4 papers), EEG and Brain-Computer Interfaces (3 papers) and Misinformation and Its Impacts (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (71 citations), Artificial Intelligence (111 citations) and Signal Processing (15 citations). Shraman Pramanick has collaborated with scholars based in India, United States and Singapore. Frequent co-authors include Md Shad Akhtar, Tanmoy Chakraborty, Shivam Sharma, Preslav Nakov, Dimitar Dimitrov, Pengchuan Zhang, Kevin Qinghong Lin, Mike Zheng Shou, Rui Yan and Difei Gao. Their work appears in journals such as Biomedical Signal Processing and Control, arXiv (Cornell University) and 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
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.