Chandramohan Dhasarathan

984 total citations
49 papers, 601 citations indexed

About

Chandramohan Dhasarathan is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Chandramohan Dhasarathan has authored 49 papers receiving a total of 601 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 23 papers in Information Systems and 15 papers in Computer Networks and Communications. Recurrent topics in Chandramohan Dhasarathan's work include Cloud Data Security Solutions (9 papers), IoT and Edge/Fog Computing (9 papers) and Blockchain Technology Applications and Security (9 papers). Chandramohan Dhasarathan is often cited by papers focused on Cloud Data Security Solutions (9 papers), IoT and Edge/Fog Computing (9 papers) and Blockchain Technology Applications and Security (9 papers). Chandramohan Dhasarathan collaborates with scholars based in India, Malaysia and Italy. Chandramohan Dhasarathan's co-authors include P. Dhavachelvan, T. Vengattaraman, G. Sambasivam, Diwakar Tripathi, J. Amudhavel, Alok Kumar Shukla, Achyut Shankar, Shailesh Khapre, Mohammad Kamrul Hasan and Shayla Islam and has published in prestigious journals such as NeuroImage, IEEE Access and Computer Communications.

In The Last Decade

Chandramohan Dhasarathan

47 papers receiving 570 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chandramohan Dhasarathan India 15 300 199 149 93 71 49 601
Mana Saleh Al Reshan Saudi Arabia 16 226 0.8× 118 0.6× 132 0.9× 119 1.3× 98 1.4× 64 702
Atif Khan Pakistan 17 564 1.9× 225 1.1× 123 0.8× 78 0.8× 101 1.4× 79 984
Ashraf Osman Ibrahim Malaysia 14 221 0.7× 122 0.6× 154 1.0× 36 0.4× 69 1.0× 72 569
N. Yuvaraj India 16 206 0.7× 85 0.4× 155 1.0× 51 0.5× 92 1.3× 50 625
Hani Alshahrani Saudi Arabia 16 242 0.8× 151 0.8× 185 1.2× 109 1.2× 98 1.4× 65 746
Y. Ding China 6 218 0.7× 133 0.7× 77 0.5× 41 0.4× 63 0.9× 13 427
Hamed Tabrizchi Iran 9 206 0.7× 230 1.2× 162 1.1× 40 0.4× 46 0.6× 24 518
Avinash Chandra Pandey India 15 508 1.7× 145 0.7× 97 0.7× 45 0.5× 198 2.8× 32 794
Mohamed Ben Ahmed Morocco 11 242 0.8× 87 0.4× 160 1.1× 72 0.8× 130 1.8× 97 570
Bader Alouffi Saudi Arabia 14 253 0.8× 303 1.5× 257 1.7× 81 0.9× 58 0.8× 30 779

Countries citing papers authored by Chandramohan Dhasarathan

Since Specialization
Citations

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

Fields of papers citing papers by Chandramohan Dhasarathan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chandramohan Dhasarathan

This figure shows the co-authorship network connecting the top 25 collaborators of Chandramohan Dhasarathan. A scholar is included among the top collaborators of Chandramohan Dhasarathan 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 Chandramohan Dhasarathan. Chandramohan Dhasarathan 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.
2.
Dhasarathan, Chandramohan, et al.. (2024). Blockchain-Based Intelligent Digital Credentialing System for Participatory Governance: Design, Implementation, and Potential Implications. SN Computer Science. 5(8). 1 indexed citations
3.
Dhasarathan, Chandramohan, et al.. (2023). Detection and classification of dermatoscopic images using segmentation and transfer learning. Multimedia Tools and Applications. 82(15). 23817–23831. 7 indexed citations
4.
Kumar, Manish, et al.. (2023). Enhancing security of IoT powered supply chain management using blockchain. 2(1). 73–86. 1 indexed citations
5.
Dhasarathan, Chandramohan, Mohammad Kamrul Hasan, Shayla Islam, et al.. (2023). User privacy prevention model using supervised federated learning‐based block chain approach for internet of Medical Things. CAAI Transactions on Intelligence Technology. 26 indexed citations
6.
Dhasarathan, Chandramohan, et al.. (2022). Energy-Aware Multilevel Clustering Scheme for Underwater Wireless Sensor Networks. IEEE Access. 10. 55868–55875. 20 indexed citations
7.
Dhasarathan, Chandramohan, et al.. (2022). A Comprehensive Review on Blockchain-Based Internet of Things (BIoT). 25–44. 1 indexed citations
8.
Dhasarathan, Chandramohan, et al.. (2022). COVID-19 identification in chest X-ray images using intelligent multi-level classification scenario. Computers & Electrical Engineering. 104. 108405–108405. 11 indexed citations
9.
Shankar, Achyut, et al.. (2022). Correction to: A modified social spider algorithm for an efficient data dissemination in VANET. Environment Development and Sustainability. 27(10). 24703–24704. 1 indexed citations
10.
Shankar, Achyut, et al.. (2022). A modified social spider algorithm for an efficient data dissemination in VANET. Environment Development and Sustainability. 27(10). 24659–24702. 16 indexed citations
11.
Dhasarathan, Chandramohan, Mohammad Kamrul Hasan, Shayla Islam, et al.. (2022). COVID-19 health data analysis and personal data preserving: A homomorphic privacy enforcement approach. Computer Communications. 199. 87–97. 40 indexed citations
12.
Dhasarathan, Chandramohan, et al.. (2021). Recent Advances in Edge Computing Paradigms. 4(1). 37–51. 1 indexed citations
13.
Dhasarathan, Chandramohan, et al.. (2021). A novel approach for multi-constraints knapsack problem using cluster particle swarm optimization. Computers & Electrical Engineering. 96. 107399–107399. 10 indexed citations
14.
Dhasarathan, Chandramohan, et al.. (2021). Evolution of Fog Computing Applications, Opportunities, and Challenges. 4(1). 1–17. 1 indexed citations
15.
Sambasivam, G., et al.. (2020). Prediction of COVID-19 Using Genetic Deep Learning Convolutional Neural Network (GDCNN). IEEE Access. 8. 177647–177666. 77 indexed citations
16.
Dhasarathan, Chandramohan, et al.. (2020). DUICM Deep Underwater Image Classification Mobdel using Convolutional Neural Networks. International Journal of Grid and High Performance Computing. 12(3). 88–100. 13 indexed citations
17.
Dhasarathan, Chandramohan, et al.. (2019). Fog enabled secure and privacy obfuscation for Iot services. Journal of Advanced Research in Dynamic and Control Systems. 11. 1604–1610. 3 indexed citations
18.
Dhasarathan, Chandramohan, et al.. (2018). A coordinator‐specific privacy‐preserving model for E‐health monitoring using artificial bee colony approach. Security and Privacy. 1(4). 11 indexed citations
19.
Dhasarathan, Chandramohan, et al.. (2018). Air Pollution Based Vehicular Routing Problems: Using Genetic Algorithm Optimization Approach. Ekoloji. 27(106). 1575–1587. 2 indexed citations
20.
Dhasarathan, Chandramohan, et al.. (2011). OPTIMIZATION OF CAPACITATED VEHICLE ROUTING PROBLEM USING PSO. 21 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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