R. Rajagopal

1.4k total citations
68 papers, 1.1k citations indexed

About

R. Rajagopal is a scholar working on Organic Chemistry, Water Science and Technology and Environmental Engineering. According to data from OpenAlex, R. Rajagopal has authored 68 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Organic Chemistry, 12 papers in Water Science and Technology and 10 papers in Environmental Engineering. Recurrent topics in R. Rajagopal's work include Water Quality and Resources Studies (11 papers), Ionic liquids properties and applications (9 papers) and Groundwater flow and contamination studies (9 papers). R. Rajagopal is often cited by papers focused on Water Quality and Resources Studies (11 papers), Ionic liquids properties and applications (9 papers) and Groundwater flow and contamination studies (9 papers). R. Rajagopal collaborates with scholars based in India, United States and Jordan. R. Rajagopal's co-authors include Kumar V. Srinivasan, Dilip V. Jarikote, Ravindra R. Deshmukh, Thomas Daniel, Rajgopal J. Lahoti, S. A. Siddiqui, Graham A. Tobin, T. M. Jyothi, B.S. Rao and Leah R. Williams and has published in prestigious journals such as Chemical Communications, Journal of Environmental Quality and Tetrahedron Letters.

In The Last Decade

R. Rajagopal

66 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
R. Rajagopal India 14 736 275 171 104 100 68 1.1k
Rima D. Alharthy Saudi Arabia 16 250 0.3× 61 0.2× 80 0.5× 65 0.6× 160 1.6× 54 941
Ritu Jain United States 10 270 0.4× 337 1.2× 195 1.1× 161 1.5× 48 0.5× 22 1.1k
Wendell L. Dilling United States 18 437 0.6× 31 0.1× 129 0.8× 80 0.8× 94 0.9× 49 1.0k
Sooridarsan Krishnan Malaysia 12 117 0.2× 93 0.3× 143 0.8× 98 0.9× 44 0.4× 21 846
T.J. Nestrick United States 17 422 0.6× 103 0.4× 135 0.8× 393 3.8× 129 1.3× 51 1.8k
Byron Kratochvil Canada 20 213 0.3× 33 0.1× 111 0.6× 172 1.7× 56 0.6× 91 1.2k
María J. Fernández‐Torres Spain 18 249 0.3× 60 0.2× 132 0.8× 231 2.2× 105 1.1× 47 812
P. Isnard France 15 436 0.6× 192 0.7× 526 3.1× 216 2.1× 110 1.1× 17 1.6k
Zhili Chen China 23 390 0.5× 23 0.1× 238 1.4× 119 1.1× 70 0.7× 99 1.6k

Countries citing papers authored by R. Rajagopal

Since Specialization
Citations

This map shows the geographic impact of R. Rajagopal'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. Rajagopal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R. Rajagopal more than expected).

Fields of papers citing papers by R. Rajagopal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R. Rajagopal. 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. Rajagopal. The network helps show where R. Rajagopal may publish in the future.

Co-authorship network of co-authors of R. Rajagopal

This figure shows the co-authorship network connecting the top 25 collaborators of R. Rajagopal. A scholar is included among the top collaborators of R. Rajagopal 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. Rajagopal. R. Rajagopal 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.
Rajagopal, R., et al.. (2024). Cluster Head Selection Using Multi-Dilation Convolutional Neural Network Optimized with BCMO for IoT Networks. IETE Journal of Research. 70(8). 6702–6710. 1 indexed citations
2.
Rajagopal, R., et al.. (2023). Facemask Detection System using CNN Model. 75. 1–6.
3.
Rajagopal, R., et al.. (2023). Enhancing Skin Cancer Diagnosis with Deep Learning-Based Classification. International Journal on Recent and Innovation Trends in Computing and Communication. 11(5s). 105–111. 3 indexed citations
4.
Anitha, V., et al.. (2023). Cybersecurity in Internet of Things Networks using Deep Learning Models. 1090–1095. 2 indexed citations
5.
Velliangiri, S., R. Rajagopal, & P. Karthikeyan. (2019). Trust Factor Based Key Distribution Protocol in Hybrid Cloud Environment. Scalable Computing Practice and Experience. 20(2). 349–364. 3 indexed citations
6.
Rajagopal, R., et al.. (2007). Economics of place-based monitoring under the safe drinking water act, part II: Design and development of place-based monitoring strategies. Environmental Monitoring and Assessment. 143(1-3). 91–102. 2 indexed citations
7.
Rajagopal, R., et al.. (2007). Economics of place-based monitoring under the safe drinking water act, part III: performance evaluation of place-based monitoring strategies. Environmental Monitoring and Assessment. 143(1-3). 103–120. 2 indexed citations
8.
Rajagopal, R. & Kumar V. Srinivasan. (2003). Regio-selective Mono Nitration of Phenols with Ferric Nitrate in Room Temperature Ionic Liquid. Synthetic Communications. 33(6). 961–966. 58 indexed citations
9.
Rajagopal, R., et al.. (2002). Target classification in a passive sonar-an expert system approach. International Conference on Acoustics, Speech, and Signal Processing. 2911–2914. 24 indexed citations
10.
Jarikote, Dilip V., Ravindra R. Deshmukh, R. Rajagopal, et al.. (2002). Ultrasound promoted facile synthesis of arylhydrazones at ambient conditions. Ultrasonics Sonochemistry. 10(1). 45–48. 9 indexed citations
11.
Rajagopal, R., Dilip V. Jarikote, & Kumar V. Srinivasan. (2002). Ultrasound promoted Suzuki cross-coupling reactions in ionic liquid at ambient conditions. Chemical Communications. 616–617. 166 indexed citations
12.
Deshmukh, Ravindra R., R. Rajagopal, & Kumar V. Srinivasan. (2001). Ultrasound promoted C–C bond formation: Heck reaction at ambient conditions in room temperature ionic liquids. Chemical Communications. 1544–1545. 246 indexed citations
13.
Rajagopal, R., et al.. (1994). Utility of Screening in Environmental Monitoring, Part 1: Occurrence and Distribution of VOCs in Groundwater. Iowa Research Online (University of Iowa). 6(4). 16. 1 indexed citations
14.
Rajagopal, R., et al.. (1991). Fluoride in drinking water: A survey of expert opinions. Environmental Geochemistry and Health. 13(1). 3–13. 19 indexed citations
15.
Rajagopal, R., et al.. (1991). Comparison of two screening methods for the detection of volatile organic compounds in ground water. Journal of Chemometrics. 5(3). 321–331. 7 indexed citations
16.
Rajagopal, R. & Graham A. Tobin. (1990). Radioactivity in drinking water: Expert opinion and policy choices. Environmental Geochemistry and Health. 12(4). 267–276. 1 indexed citations
17.
Rajagopal, R. & Leah R. Williams. (1989). Economics of Sample Compositing as a Screening Tool in Ground Water Quality Monitoring. Groundwater Monitoring & Remediation. 9(1). 186–192. 10 indexed citations
18.
Rajagopal, R.. (1986). The Effect of Sampling Frequency on Ground Water Quality Characterization. Groundwater Monitoring & Remediation. 6(4). 65–73. 7 indexed citations
19.
Rajagopal, R.. (1984). Optimal sampling strategies for source identification in environmental episodes. Environmental Monitoring and Assessment. 4(1). 1–14. 7 indexed citations
20.
Rajagopal, R., et al.. (1975). Water Quality and Economic Criteria for Rural Wastewater and Water Supply Systems. Iowa Research Online (University of Iowa). 47(7). 1834. 1 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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