Rakesh Kumar Mahendran
- Computer Networks and Communications top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Plant Science
- Co-authors
- V. ParthasarathyMuhammad ShafiqJin‐Ghoo ChoiArfat Ahmad KhanR. SanthoshSalman NaseerP KumarMuhammad Faheem
- Topics
- Blind Source Separation Techniques (6 papers)EEG and Brain-Computer Interfaces (6 papers)IoT and Edge/Fog Computing (5 papers)
- Partner nations
- IndiaSaudi ArabiaThailand
In The Last Decade
Rakesh Kumar Mahendran
29 papers receiving 581 citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Computer Networks and Communications 119
- Artificial Intelligence 108
- Computer Vision and Pattern Recognition 92
- Information Systems 89
- Plant Science 87
Countries citing papers authored by Rakesh Kumar Mahendran
This map shows the geographic impact of Rakesh Kumar Mahendran'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 Rakesh Kumar Mahendran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rakesh Kumar Mahendran more than expected).
Fields of papers citing papers by Rakesh Kumar Mahendran
This network shows the impact of papers produced by Rakesh Kumar Mahendran. 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 Rakesh Kumar Mahendran. The network helps show where Rakesh Kumar Mahendran may publish in the future.
Co-authorship network of co-authors of Rakesh Kumar Mahendran
This figure shows the co-authorship network connecting the top 25 collaborators of Rakesh Kumar Mahendran. A scholar is included among the top collaborators of Rakesh Kumar Mahendran 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 Rakesh Kumar Mahendran. Rakesh Kumar Mahendran is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 4 | |
| 8 | 10 | |
| 9 | 0 | |
| 10 | 30 | |
| 11 | 7 | |
| 12 | 7 | |
| 13 | 4 | |
| 14 | 18 | |
| 15 | 28 | |
| 16 | 61 | |
| 17 | 3 | |
| 18 | 12 | |
| 19 | 1 | |
| 20 | 2 |
About Rakesh Kumar Mahendran
Rakesh Kumar Mahendran is a scholar working on Signal Processing, Health Informatics and Computer Networks and Communications, having authored 38 papers that have together received 605 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (6 papers), EEG and Brain-Computer Interfaces (6 papers) and IoT and Edge/Fog Computing (5 papers). The work is most often cited by research in Health Informatics (13 citations), Signal Processing (67 citations) and Computer Networks and Communications (119 citations). Rakesh Kumar Mahendran has collaborated with scholars based in India, Saudi Arabia and Thailand. Frequent co-authors include V. Parthasarathy, Muhammad Shafiq, Jin‐Ghoo Choi, Arfat Ahmad Khan, R. Santhosh, Salman Naseer, P Kumar, Muhammad Faheem, Navod Neranjan Thilakarathne and Seifedine Kadry. Their work appears in journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.
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.