Suju Rajan
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 1%
- Information Systems top 5%
- Atmospheric Science
- Co-authors
- Joydeep GhoshMelba M. CrawfordVijay K. NarayananLei TangErheng ZhongLiangjie HongYi XingKunal Punera
- Topics
- Text and Document Classification Technologies (7 papers)Advanced Image and Video Retrieval Techniques (4 papers)Recommender Systems and Techniques (4 papers)
- Journals
- IEEE Transactions on Geoscience and Remote SensingUvA-DARE (University of Amsterdam)National Conference on Artificial Intelligence
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Suju Rajan
19 papers receiving 711 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 399
- Computer Vision and Pattern Recognition 279
- Media Technology 269
- Information Systems 210
- Atmospheric Science 96
Countries citing papers authored by Suju Rajan
This map shows the geographic impact of Suju Rajan'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 Suju Rajan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suju Rajan more than expected).
Fields of papers citing papers by Suju Rajan
This network shows the impact of papers produced by Suju Rajan. 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 Suju Rajan. The network helps show where Suju Rajan may publish in the future.
Co-authorship network of co-authors of Suju Rajan
This figure shows the co-authorship network connecting the top 25 collaborators of Suju Rajan. A scholar is included among the top collaborators of Suju Rajan 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 Suju Rajan. Suju Rajan 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 | 1 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 8 | |
| 8 | 26 | |
| 9 | 2 | |
| 10 | 20 | |
| 11 | 145 | |
| 12 | 15 | |
| 13 | 123 | |
| 14 | 1 | |
| 15 | 245 | |
| 16 | 9 | |
| 17 | 77 | |
| 18 | 19 | |
| 19 | A maximum likelihood framework for integrating taxonomies | 5 |
| 20 | 36 |
About Suju Rajan
Suju Rajan is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 21 papers that have together received 747 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (7 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Recommender Systems and Techniques (4 papers). The work is most often cited by research in Media Technology (269 citations), Computer Vision and Pattern Recognition (279 citations) and Artificial Intelligence (399 citations). Suju Rajan has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Joydeep Ghosh, Melba M. Crawford, Vijay K. Narayanan, Lei Tang, Erheng Zhong, Liangjie Hong, Yi Xing, Kunal Punera, Nathan Liu and Yue Shi. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, UvA-DARE (University of Amsterdam) 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.