Suju Rajan

1.1k total citations
21 papers, 747 citations indexed

About

Suju Rajan is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Suju Rajan has authored 21 papers receiving a total of 747 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 9 papers in Information Systems and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Suju Rajan's work include Text and Document Classification Technologies (7 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Recommender Systems and Techniques (4 papers). Suju Rajan is often cited by papers focused on Text and Document Classification Technologies (7 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Recommender Systems and Techniques (4 papers). Suju Rajan collaborates with scholars based in United States, Australia and United Kingdom. Suju Rajan's 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 and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, UvA-DARE (University of Amsterdam) and National Conference on Artificial Intelligence.

In The Last Decade

Suju Rajan

19 papers receiving 711 citations

Peers

Suju Rajan
Weiwei Liu China
Caihong Mu China
Greg Pass United States
Kan Xu China
Yeqing Li United States
Zhongliang Wei China
Hong Peng China
Daniela Zaharie Romania
Stefan A. Robila United States
Weiwei Liu China
Suju Rajan
Citations per year, relative to Suju Rajan Suju Rajan (= 1×) peers Weiwei Liu

Countries citing papers authored by Suju Rajan

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Akilandeswari, S., et al.. (2025). A Hybrid CNN-LSTM-PSO Framework for Enhanced Cybersecurity Threat Detection and Classification. 1956–1965. 1 indexed citations
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Bansal, Mamta, et al.. (2021). Retraction Notice to: Recent Approaches for Text Summarization Using Machine Learning & LSTM0. 3(2). 97–97. 1 indexed citations
5.
Rajan, Suju. (2017). The Evolution of Computational Advertising. 99–99. 2 indexed citations
6.
Yu, Rose, et al.. (2016). Geographic Segmentation via Latent Poisson Factor Model. 357–366. 2 indexed citations
7.
Zhong, Erheng, Yue Shi, Nathan Liu, & Suju Rajan. (2016). Scaling Factorization Machines with Parameter Server. 1583–1592. 8 indexed citations
8.
Ahn, Sungjin, Anoop Korattikara, Nathan Liu, Suju Rajan, & Max Welling. (2015). Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC. UvA-DARE (University of Amsterdam). 9–18. 26 indexed citations
9.
Qian, Mingjie, Liangjie Hong, Yue Shi, & Suju Rajan. (2015). Structured Sparse Regression for Recommender Systems. 1895–1898. 2 indexed citations
10.
Zhong, Erheng, Nathan Liu, Yue Shi, & Suju Rajan. (2015). Building Discriminative User Profiles for Large-scale Content Recommendation. 2277–2286. 20 indexed citations
11.
Xing, Yi, et al.. (2014). Beyond clicks. 113–120. 145 indexed citations
12.
Vadrevu, Srinivas, Choon Hui Teo, Suju Rajan, et al.. (2011). Scalable clustering of news search results. 675–684. 15 indexed citations
13.
Tang, Lei, Suju Rajan, & Vijay K. Narayanan. (2009). Large scale multi-label classification via metalabeler. 211–220. 123 indexed citations
14.
Punera, Kunal & Suju Rajan. (2009). Improved Multi Label Classification in Hierarchical Taxonomies. 5. 388–393. 1 indexed citations
15.
Rajan, Suju, Joydeep Ghosh, & Melba M. Crawford. (2008). An Active Learning Approach to Hyperspectral Data Classification. IEEE Transactions on Geoscience and Remote Sensing. 46(4). 1231–1242. 245 indexed citations
16.
Rajan, Suju, Joydeep Ghosh, & Melba M. Crawford. (2006). An Active Learning Approach to Knowledge Transfer for Hyperspectral Data Analysis. 541–544. 9 indexed citations
17.
Rajan, Suju, Joydeep Ghosh, & Melba M. Crawford. (2006). Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data. IEEE Transactions on Geoscience and Remote Sensing. 44(11). 3408–3417. 77 indexed citations
18.
Punera, Kunal, Suju Rajan, & Joydeep Ghosh. (2006). Automatic Construction of N-ary Tree Based Taxonomies. 75–79. 19 indexed citations
19.
Rajan, Suju, Kunal Punera, & Joydeep Ghosh. (2005). A maximum likelihood framework for integrating taxonomies. National Conference on Artificial Intelligence. 856–861. 5 indexed citations
20.
Punera, Kunal, Suju Rajan, & Joydeep Ghosh. (2005). Automatically learning document taxonomies for hierarchical classification. 1010–1010. 36 indexed citations

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.

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