Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of R. K. Agrawal'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 R. K. Agrawal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R. K. Agrawal more than expected).
This network shows the impact of papers produced by R. K. Agrawal. 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 R. K. Agrawal. The network helps show where R. K. Agrawal may publish in the future.
Co-authorship network of co-authors of R. K. Agrawal
This figure shows the co-authorship network connecting the top 25 collaborators of R. K. Agrawal.
A scholar is included among the top collaborators of R. K. Agrawal 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 R. K. Agrawal. R. K. Agrawal is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Rana, Bharti, et al.. (2013). Detection of Alzheimer's Disease via Statistical Features from Brain Slices.. The Florida AI Research Society.1 indexed citations
10.
Agrawal, R. K., et al.. (2012). Implementation of identity based distributed cloud storage encryption scheme using PHP and C for Hadoop File System. IEEE International Conference on High Performance Computing, Data, and Analytics. 74–77.1 indexed citations
11.
Agrawal, R. K., et al.. (2012). CLUSTERING IN CONJUNCTION WITH WRAPPER APPROACH TO SELECT DISCRIMINATORY GENES FOR MICROARRAY DATASET CLASSIFICATION. Computing and Informatics / Computers and Artificial Intelligence. 31(5). 921–938.2 indexed citations
12.
Adhikari, Ratnadip & R. K. Agrawal. (2011). A Homogeneous Ensemble of Artificial Neural Networks for Time Series Forecasting. arXiv (Cornell University). 32(7). 1–8.14 indexed citations
13.
Adhikari, Ratnadip & R. K. Agrawal. (2011). Effectiveness of PSO Based Neural Network for Seasonal Time Series Forecasting.. Indian International Conference on Artificial Intelligence. 231–244.27 indexed citations
14.
Verma, Hanuman & R. K. Agrawal. (2011). Automatic Segmentation of MRI Brain Image using Type-3 Fuzzy C-Means Clustering Algorithm.. Indian International Conference on Artificial Intelligence. 1060–1069.2 indexed citations
15.
Bala, Manju & R. K. Agrawal. (2009). Decision Tree SVM Framework Using Ratio of Interclass and Intraclass Scatters.. Indian International Conference on Artificial Intelligence. 2198–2206.1 indexed citations
Agrawal, R. K. & H. V. Jagadish. (1989). On correctly configuring versioned objects. Very Large Data Bases. 367–374.11 indexed citations
20.
Agrawal, R. K. & Narain Gehani. (1989). Rationale for the design of persistence and query processing facilities in the database programming language O. 25–40.36 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.