Yaman Kumar
- Artificial Intelligence top 10%
- Signal Processing
- Information Systems
- Computer Vision and Pattern Recognition
- Computer Science Applications
- Co-authors
- Rajiv Ratn ShahDebanjan MahataRoger ZimmermannSwati AggarwalChangyou ChenPonnurangam KumaraguruHaimin ZhangBalaji Krishnamurthy
- Topics
- Topic Modeling (11 papers)Natural Language Processing Techniques (8 papers)Speech and Audio Processing (4 papers)
- Journals
- Language Resources and EvaluationInternational Journal of Artificial Intelligence in EducationProceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- IndiaUnited StatesSingapore
In The Last Decade
Yaman Kumar
21 papers receiving 140 citations
Peers
Comparison fields: 5 of 39
- Artificial Intelligence 111
- Signal Processing 34
- Information Systems 25
- Computer Vision and Pattern Recognition 25
- Computer Science Applications 13
Countries citing papers authored by Yaman Kumar
This map shows the geographic impact of Yaman Kumar'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 Yaman Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaman Kumar more than expected).
Fields of papers citing papers by Yaman Kumar
This network shows the impact of papers produced by Yaman Kumar. 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 Yaman Kumar. The network helps show where Yaman Kumar may publish in the future.
Co-authorship network of co-authors of Yaman Kumar
This figure shows the co-authorship network connecting the top 25 collaborators of Yaman Kumar. A scholar is included among the top collaborators of Yaman Kumar 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 Yaman Kumar. Yaman Kumar 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 | 1 | |
| 5 | 5 | |
| 6 | 3 | |
| 7 | 6 | |
| 8 | 10 | |
| 9 | 6 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 10 | |
| 13 | 2 | |
| 14 | 2 | |
| 15 | An Annotated Dataset of Discourse Modes in Hindi Stories | 3 |
| 16 | 5 | |
| 17 | 7 | |
| 18 | 6 | |
| 19 | 38 | |
| 20 | 10 |
About Yaman Kumar
Yaman Kumar is a scholar working on Health Informatics, Signal Processing and Artificial Intelligence, having authored 24 papers that have together received 155 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (8 papers) and Speech and Audio Processing (4 papers). The work is most often cited by research in Artificial Intelligence (111 citations), Signal Processing (34 citations) and Computer Science Applications (13 citations). Yaman Kumar has collaborated with scholars based in India, United States and Singapore. Frequent co-authors include Rajiv Ratn Shah, Debanjan Mahata, Roger Zimmermann, Swati Aggarwal, Changyou Chen, Ponnurangam Kumaraguru, Haimin Zhang, Balaji Krishnamurthy, Karan Uppal and Yifang Yin. Their work appears in journals such as Language Resources and Evaluation, International Journal of Artificial Intelligence in Education 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.