Saloni Potdar
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Information Systems
- Computer Science Applications
- Signal Processing
- Topics
- Topic Modeling (11 papers)Natural Language Processing Techniques (8 papers)Sentiment Analysis and Opinion Mining (3 papers)
- Cited by
- Artificial IntelligenceComputer Science ApplicationsComputer Vision and Pattern Recognition
- Journals
- Transactions of the Association for Computational LinguisticsIRIS Research product catalog (Sapienza University of Rome)Proceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- United StatesItaly
In The Last Decade
Saloni Potdar
14 papers receiving 198 citations
Peers
Comparison fields: 5 of 39
- Artificial Intelligence 178
- Computer Vision and Pattern Recognition 38
- Information Systems 24
- Computer Science Applications 11
- Signal Processing 8
Countries citing papers authored by Saloni Potdar
This map shows the geographic impact of Saloni Potdar'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 Saloni Potdar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saloni Potdar more than expected).
Fields of papers citing papers by Saloni Potdar
This network shows the impact of papers produced by Saloni Potdar. 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 Saloni Potdar. The network helps show where Saloni Potdar may publish in the future.
Co-authorship network of co-authors of Saloni Potdar
This figure shows the co-authorship network connecting the top 25 collaborators of Saloni Potdar. A scholar is included among the top collaborators of Saloni Potdar 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 Saloni Potdar. Saloni Potdar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 51 | |
| 8 | 9 | |
| 9 | 12 | |
| 10 | 5 | |
| 11 | 15 | |
| 12 | 26 | |
| 13 | 63 | |
| 14 | 18 |
About Saloni Potdar
Saloni Potdar is a scholar working on Artificial Intelligence, General Social Sciences and Computer Science Applications, having authored 14 papers that have together received 209 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (8 papers) and Sentiment Analysis and Opinion Mining (3 papers). The work is most often cited by research in Artificial Intelligence (178 citations), Computer Science Applications (11 citations) and Computer Vision and Pattern Recognition (38 citations). Saloni Potdar has collaborated with scholars based in United States and Italy. Frequent co-authors include Feifei Zhai, Bowen Zhou, Bing Xiang, Lin Pan, Chung-Wei Hang, Avirup Sil, Mo Yu, Ming Tan, Lara J. Martin and Dakuo Wang. Their work appears in journals such as Transactions of the Association for Computational Linguistics, IRIS Research product catalog (Sapienza University of Rome) and Proceedings of the AAAI 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.