Supriya Supriya

1.0k citations
14 papers · 653 indexed · 1 hit paper · h-index 7

Supriya Supriya

12 papers receiving 610 citations

Hit Papers

A Study of Encryption Algorithms (RSA, DES, 3DES and AES)...260201320262017202150100150200250

Peers

Supriya Supriya
Comparison fields: 5 of 78
  • Cognitive Neuroscience 298
  • Signal Processing 150
  • Computer Vision and Pattern Recognition 171
  • Artificial Intelligence 175
  • Information Systems 84
Replace Mohammad-Parsa Hosseini with:
Mohammad-Parsa Hosseini United States
P. S. Sathidevi India
Hisham Daoud United States
Hatim Aboalsamh Saudi Arabia
Wenyu Wang China
Xinchun Cui China
Hong He China
Mohamed Kholief Egypt
Tongguang Ni China
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Supriya Supriya relative to Mohammad-Parsa Hosseini United States Mohammad-Parsa Hosseini's profile →
Citations per field
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Citations per year

Countries citing papers authored by Supriya Supriya

Since Specialization
Citations

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

Fields of papers citing papers by Supriya Supriya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 6 scholars most cited alongside Supriya Supriya, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Supriya Supriya Line = papers co-authored together Supriya Supriya links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 20250
2 20231
3 20210
4 202116
5 20212
6 202166
7 202063
8 201846
9 20171
10 20171
11 2016155
12 201636
13
A Study of Encryption Algorithms (RSA, DES, 3DES and AES) for Information Securitybreakdown →
2013260
14
Electronic Braille pad
20096

About Supriya Supriya

Supriya Supriya is a scholar working on Energy Engineering and Power Technology, Cognitive Neuroscience and Aquatic Science, having authored 14 papers that have together received 653 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (7 papers), Functional Brain Connectivity Studies (5 papers), Neural dynamics and brain function (3 papers), Hybrid Renewable Energy Systems (2 papers), Aquatic life and conservation (2 papers), Food and Agricultural Sciences (2 papers), Energy and Environment Impacts (2 papers) and Epilepsy research and treatment (1 paper). The work is most often cited by research in Cognitive Neuroscience (298 citations), Signal Processing (150 citations) and Computer Vision and Pattern Recognition (171 citations). Supriya Supriya has collaborated with scholars based in Australia, India and Indonesia. Frequent co-authors include Gurpreet Singh, Siuly Siuly, Hua Wang, Yanchun Zhang, Jinli Cao and P.C. Pant. Their work appears in journals such as IEEE Reviews in Biomedical Engineering, Health Information Science and Systems, Applied Acoustics, Electronics Letters and Sensors.

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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