M. Gunasekaran
- Computer Networks and Communications top 10%
- Information Systems top 10%
- Artificial Intelligence
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition
- Co-authors
- Mohamed ElhosenyHamid Reza BoveiriRaouf KhayamiK. PremalathaXiaohui YuanMai MohamedFlorentín SmarandacheMona Gafar
- Topics
- Anomaly Detection Techniques and Applications (9 papers)Adversarial Robustness in Machine Learning (7 papers)Stock Market Forecasting Methods (6 papers)
- Cited by
- Computer Networks and CommunicationsInformation SystemsManagement Science and Operations Research
- Journals
- Neural Computing and ApplicationsAlexandria Engineering JournalMobile Networks and Applications
- Partner nations
- IndiaUnited StatesEgypt
In The Last Decade
M. Gunasekaran
38 papers receiving 231 citations
Peers
Comparison fields: 5 of 71
- Computer Networks and Communications 116
- Information Systems 65
- Artificial Intelligence 62
- Electrical and Electronic Engineering 48
- Computer Vision and Pattern Recognition 27
Countries citing papers authored by M. Gunasekaran
This map shows the geographic impact of M. Gunasekaran'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 M. Gunasekaran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Gunasekaran more than expected).
Fields of papers citing papers by M. Gunasekaran
This network shows the impact of papers produced by M. Gunasekaran. 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 M. Gunasekaran. The network helps show where M. Gunasekaran may publish in the future.
Co-authorship network of co-authors of M. Gunasekaran
This figure shows the co-authorship network connecting the top 25 collaborators of M. Gunasekaran. A scholar is included among the top collaborators of M. Gunasekaran 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 M. Gunasekaran. M. Gunasekaran is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 0 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 3 | |
| 17 | Microcontroller based fitness analysis using IOT | 1 |
| 18 | PORTFOLIO OPTIMIZATION USING NEURO FUZZY SYSTEM IN INDIAN STOCK MARKET | 0 |
| 19 | A Fusion Model Integrating ANFIS and Artificial Immune Algorithm for Forecasting Indian Stock Market | 2 |
| 20 | 1 |
About M. Gunasekaran
M. Gunasekaran is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Networks and Communications, having authored 50 papers that have together received 258 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (9 papers), Adversarial Robustness in Machine Learning (7 papers) and Stock Market Forecasting Methods (6 papers). The work is most often cited by research in Computer Networks and Communications (116 citations), Information Systems (65 citations) and Management Science and Operations Research (24 citations). M. Gunasekaran has collaborated with scholars based in India, United States and Egypt. Frequent co-authors include Mohamed Elhoseny, Hamid Reza Boveiri, Raouf Khayami, K. Premalatha, Xiaohui Yuan, Mai Mohamed, Florentín Smarandache, Mona Gafar, Mohamed Abdel‐Basset and Gopalakrishnan Balasubramanian. Their work appears in journals such as Neural Computing and Applications, Alexandria Engineering Journal and Mobile Networks and Applications.
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.