S Supreeth

439 total citations
47 papers, 208 citations indexed

About

S Supreeth is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, S Supreeth has authored 47 papers receiving a total of 208 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Networks and Communications, 15 papers in Artificial Intelligence and 14 papers in Information Systems. Recurrent topics in S Supreeth's work include IoT and Edge/Fog Computing (11 papers), Cloud Computing and Resource Management (11 papers) and Chaos-based Image/Signal Encryption (6 papers). S Supreeth is often cited by papers focused on IoT and Edge/Fog Computing (11 papers), Cloud Computing and Resource Management (11 papers) and Chaos-based Image/Signal Encryption (6 papers). S Supreeth collaborates with scholars based in India, United Kingdom and Bahrain. S Supreeth's co-authors include Kiran Kumari Patil, Monica R. Mundada, P. Dayananda, Bryan Gardiner, Anita Kanavalli, Harish Hanumanthappa, Rajeev Ranjan, B. Sujatha, Harini Ramaprasad and Shweta Kumari and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

S Supreeth

36 papers receiving 196 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S Supreeth India 10 102 77 48 36 28 47 208
N. Jagadish Kumar India 11 100 1.0× 95 1.2× 51 1.1× 33 0.9× 11 0.4× 30 276
Michele Sevegnani United Kingdom 8 60 0.6× 24 0.3× 60 1.3× 13 0.4× 10 0.4× 28 171
Yuwei Xu China 11 128 1.3× 61 0.8× 91 1.9× 45 1.3× 25 0.9× 38 268
Biresh Kumar India 8 46 0.5× 59 0.8× 44 0.9× 39 1.1× 9 0.3× 52 195
Satyabrata Das India 9 197 1.9× 115 1.5× 31 0.6× 18 0.5× 8 0.3× 35 251
Chien-Chang Liu Taiwan 8 201 2.0× 148 1.9× 75 1.6× 25 0.7× 16 0.6× 15 286
Sathish Kumar United States 10 114 1.1× 84 1.1× 72 1.5× 14 0.4× 7 0.3× 26 232
Kuldeep Narayan Tripathi India 9 152 1.5× 88 1.1× 49 1.0× 33 0.9× 19 0.7× 24 214
Isaac Odun-Ayo Nigeria 11 137 1.3× 180 2.3× 55 1.1× 17 0.5× 6 0.2× 42 272
Mahshid Helali Moghadam Sweden 8 84 0.8× 42 0.5× 68 1.4× 13 0.4× 7 0.3× 27 204

Countries citing papers authored by S Supreeth

Since Specialization
Citations

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

Fields of papers citing papers by S Supreeth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S Supreeth

This figure shows the co-authorship network connecting the top 25 collaborators of S Supreeth. A scholar is included among the top collaborators of S Supreeth 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 S Supreeth. S Supreeth 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.
Supreeth, S, et al.. (2025). A secure and energy-efficient routing using coupled ensemble selection approach and optimal type-2 fuzzy logic in WSN. Scientific Reports. 15(1). 38–38. 4 indexed citations
3.
Fernandes, Roshan, et al.. (2025). Brain Tumour Detection Using VGG‐Based Feature Extraction With Modified DarkNet‐53 Model. International Journal of Biomedical Imaging. 2025(1). 5535505–5535505.
4.
Supreeth, S, et al.. (2025). Leveraging machine learning for intelligent agriculture. SHILAP Revista de lepidopterología. 5(1). 4 indexed citations
5.
Supreeth, S, et al.. (2025). Air quality and dust level monitoring systems in hospitals using IoT. SHILAP Revista de lepidopterología. 5(1).
6.
Supreeth, S, et al.. (2024). A Machine Learning Approach for Environmental Assessment on Air Quality and Mitigation Strategy. Journal of Engineering. 2024(1). 6 indexed citations
9.
Supreeth, S, et al.. (2024). Optimizing Security: A Comparative Analysis of RSA, ECC, and DH Algorithms. 1–6. 3 indexed citations
10.
Dayananda, P., et al.. (2024). Hybrid RNN Based Text Classification Model for Unstructured Data. SN Computer Science. 5(6). 2 indexed citations
11.
Dayananda, P., et al.. (2024). A Visual Computing Unified Application Using Deep Learning and Computer Vision Techniques. International Journal of Interactive Mobile Technologies (iJIM). 18(1). 59–74. 3 indexed citations
13.
15.
Mundada, Monica R., et al.. (2023). An Efficient Framework for Web Content Mining Systems Using Improved CD-PAM Clustering and the A-CNN Technique. SN Computer Science. 4(5). 1 indexed citations
16.
Supreeth, S, et al.. (2023). Virtual Machine Placement Using Adam White Shark Optimization Algorithm in Cloud Computing. SN Computer Science. 5(1). 3 indexed citations
17.
Supreeth, S, et al.. (2022). An Efficient Policy-Based Scheduling and Allocation of Virtual Machines in Cloud Computing Environment. Journal of Electrical and Computer Engineering. 2022. 1–12. 8 indexed citations
19.
20.
Supreeth, S, et al.. (2019). Traffic Management using Convolution Neural Network. International Journal of Engineering and Advanced Technology. 8(5s). 146–149. 9 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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