Varun Manjunatha
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 10%
- Management Science and Operations Research top 10%
- Signal Processing
- Co-authors
- Mohit IyyerJordan Boyd‐GraberHal DauméRajiv JainVlad I. MorariuCurtis WigingtonVicente OrdóñezVishal M. Patel
- Topics
- Topic Modeling (8 papers)Natural Language Processing Techniques (7 papers)Multimodal Machine Learning Applications (6 papers)
- Journals
- ACM Transactions on Accessible ComputingIndonesian Journal of Electrical Engineering and Computer ScienceFindings of the Association for Computational Linguistics: ACL 2022
- Partner nations
- United StatesMexicoIndia
In The Last Decade
Varun Manjunatha
14 papers receiving 798 citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 678
- Computer Vision and Pattern Recognition 242
- Information Systems 80
- Management Science and Operations Research 44
- Signal Processing 37
Countries citing papers authored by Varun Manjunatha
This map shows the geographic impact of Varun Manjunatha'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 Varun Manjunatha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Varun Manjunatha more than expected).
Fields of papers citing papers by Varun Manjunatha
This network shows the impact of papers produced by Varun Manjunatha. 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 Varun Manjunatha. The network helps show where Varun Manjunatha may publish in the future.
Co-authorship network of co-authors of Varun Manjunatha
This figure shows the co-authorship network connecting the top 25 collaborators of Varun Manjunatha. A scholar is included among the top collaborators of Varun Manjunatha 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 Varun Manjunatha. Varun Manjunatha 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | 6 | |
| 9 | 63 | |
| 10 | 0 | |
| 11 | 65 | |
| 12 | 44 | |
| 13 | 21 | |
| 14 | 25 | |
| 15 | 119 | |
| 16 | 42 | |
| 17 | Deep Unordered Composition Rivals Syntactic Methods for Text Classificationbreakdown → | 448 |
| 18 | 2 |
About Varun Manjunatha
Varun Manjunatha is a scholar working on Human Factors and Ergonomics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 18 papers that have together received 847 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (7 papers) and Multimodal Machine Learning Applications (6 papers). The work is most often cited by research in Artificial Intelligence (678 citations), Computer Vision and Pattern Recognition (242 citations) and Information Systems (80 citations). Varun Manjunatha has collaborated with scholars based in United States, Mexico and India. Frequent co-authors include Mohit Iyyer, Jordan Boyd‐Graber, Hal Daumé, Rajiv Jain, Vlad I. Morariu, Curtis Wigington, Vicente Ordóñez, Vishal M. Patel, Pramuditha Perera and Jiuxiang Gu. Their work appears in journals such as ACM Transactions on Accessible Computing, Indonesian Journal of Electrical Engineering and Computer Science and Findings of the Association for Computational Linguistics: ACL 2022.
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.