Harsh Jhamtani
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Information Systems
- Sociology and Political Science
- Economics and Econometrics
- Co-authors
- Taylor Berg-KirkpatrickVarun GangalVaskar RaychoudhuryEduard HovyGraham NeubigPrakhar GuptaJeffrey P. BighamJaime Carbonell
- Topics
- Topic Modeling (8 papers)Natural Language Processing Techniques (8 papers)Speech and dialogue systems (4 papers)
- Journals
- arXiv (Cornell University)Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Partner nations
- United StatesIndiaSwitzerland
In The Last Decade
Harsh Jhamtani
13 papers receiving 98 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 81
- Computer Vision and Pattern Recognition 22
- Information Systems 13
- Sociology and Political Science 12
- Economics and Econometrics 7
Countries citing papers authored by Harsh Jhamtani
This map shows the geographic impact of Harsh Jhamtani'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 Harsh Jhamtani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harsh Jhamtani more than expected).
Fields of papers citing papers by Harsh Jhamtani
This network shows the impact of papers produced by Harsh Jhamtani. 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 Harsh Jhamtani. The network helps show where Harsh Jhamtani may publish in the future.
Co-authorship network of co-authors of Harsh Jhamtani
This figure shows the co-authorship network connecting the top 25 collaborators of Harsh Jhamtani. A scholar is included among the top collaborators of Harsh Jhamtani 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 Harsh Jhamtani. Harsh Jhamtani 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 | 1 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 2 | |
| 6 | 10 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 7 | |
| 10 | 7 | |
| 11 | 16 | |
| 12 | 3 | |
| 13 | Word-level Language Identification in Bi-lingual Code-switched Texts | 18 |
| 14 | 22 |
About Harsh Jhamtani
Harsh Jhamtani is a scholar working on Artificial Intelligence, Human-Computer Interaction and Computer Vision and Pattern Recognition, having authored 14 papers that have together received 102 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (8 papers) and Speech and dialogue systems (4 papers). The work is most often cited by research in Artificial Intelligence (81 citations), Computer Vision and Pattern Recognition (22 citations) and Information Systems (13 citations). Harsh Jhamtani has collaborated with scholars based in United States, India and Switzerland. Frequent co-authors include Taylor Berg-Kirkpatrick, Varun Gangal, Vaskar Raychoudhury, Eduard Hovy, Graham Neubig, Prakhar Gupta, Jeffrey P. Bigham, Jaime Carbonell, Bodhisattwa Prasad Majumder and Julian McAuley. Their work appears in journals such as arXiv (Cornell University), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
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.