Kanthashree Mysore Sathyendra
- Artificial Intelligence top 5%
- Sociology and Political Science top 10%
- Information Systems top 10%
- Computer Vision and Pattern Recognition top 10%
- Signal Processing top 10%
- Co-authors
- Shomir WilsonFlorian SchaubNorman SadehSebastian ZimmeckDheeraj RajagopalDevendra Singh ChaplotRuslan SalakhutdinovRama Kumar Pasumarthi
- Topics
- Topic Modeling (9 papers)Speech Recognition and Synthesis (8 papers)Natural Language Processing Techniques (8 papers)
- Journals
- ACM Transactions on the WebarXiv (Cornell University)National Conference on Artificial Intelligence
- Partner nations
- United StatesSwitzerland
In The Last Decade
Kanthashree Mysore Sathyendra
14 papers receiving 409 citations
Peers
Comparison fields: 5 of 47
- Artificial Intelligence 277
- Sociology and Political Science 216
- Information Systems 106
- Computer Vision and Pattern Recognition 85
- Signal Processing 63
Countries citing papers authored by Kanthashree Mysore Sathyendra
This map shows the geographic impact of Kanthashree Mysore Sathyendra'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 Kanthashree Mysore Sathyendra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanthashree Mysore Sathyendra more than expected).
Fields of papers citing papers by Kanthashree Mysore Sathyendra
This network shows the impact of papers produced by Kanthashree Mysore Sathyendra. 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 Kanthashree Mysore Sathyendra. The network helps show where Kanthashree Mysore Sathyendra may publish in the future.
Co-authorship network of co-authors of Kanthashree Mysore Sathyendra
This figure shows the co-authorship network connecting the top 25 collaborators of Kanthashree Mysore Sathyendra. A scholar is included among the top collaborators of Kanthashree Mysore Sathyendra 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 Kanthashree Mysore Sathyendra. Kanthashree Mysore Sathyendra 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 | 3 | |
| 5 | 29 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 6 | |
| 9 | 31 | |
| 10 | 80 | |
| 11 | 3 | |
| 12 | 29 | |
| 13 | 58 | |
| 14 | Automatic extraction of opt-out choices from privacy policies | 14 |
| 15 | 164 |
About Kanthashree Mysore Sathyendra
Kanthashree Mysore Sathyendra is a scholar working on Artificial Intelligence, Computer Science Applications and Computer Vision and Pattern Recognition, having authored 15 papers that have together received 429 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Speech Recognition and Synthesis (8 papers) and Natural Language Processing Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (277 citations), Signal Processing (63 citations) and Sociology and Political Science (216 citations). Kanthashree Mysore Sathyendra has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Shomir Wilson, Florian Schaub, Norman Sadeh, Sebastian Zimmeck, Dheeraj Rajagopal, Devendra Singh Chaplot, Ruslan Salakhutdinov, Rama Kumar Pasumarthi, Frederick Liu and Mads Schaarup Andersen. Their work appears in journals such as ACM Transactions on the Web, arXiv (Cornell University) and National Conference on Artificial Intelligence.
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.