R. Manikandan
- Health Informatics top 2%
-
- IoT and Edge/Fog Computing 17
- Energy Efficient Wireless Sensor Networks 8
- Network Security and Intrusion Detection 7
-
- Artificial Intelligence in Healthcare 10
- Artificial Intelligence top 2%
- AI in cancer detection 10
- Neurology top 5%
- Brain Tumor Detection and Classification 11
-
- COVID-19 diagnosis using AI 15
-
- VLSI and FPGA Design Techniques 7
- Co-authors
- Jafar A. AlzubiAmir H. GandomiRizwan PatanOmar A. AlzubiRamesh SekaranDeepak GuptaAmbeshwar KumarAshish Singh
- Journals
- SHILAP Revista de lepidopterología (2 papers)Scientific Reports (3 papers)Expert Systems with Applications (2 papers)
- Partner nations
- IndiaAustraliaUnited States
In The Last Decade
R. Manikandan
138 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Health Informatics 55
- Computer Networks and Communications 585
- Health Information Management 115
- Artificial Intelligence 687
- Neurology 178
Countries citing papers authored by R. Manikandan
This map shows the geographic impact of R. Manikandan'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 R. Manikandan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R. Manikandan more than expected).
Fields of papers citing papers by R. Manikandan
This network shows the impact of papers produced by R. Manikandan. 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 R. Manikandan. The network helps show where R. Manikandan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside R. Manikandan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 4 | |
| 3 | 2024 | 8 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 16 | |
| 7 | 2023 | 14 | |
| 8 | 2023 | 14 | |
| 9 | 2022 | 2 | |
| 10 | 2022 | 12 | |
| 11 | 2021 | 9 | |
| 12 | 2021 | 6 | |
| 13 | 2020 | 29 | |
| 14 | 2020 | 67 | |
| 15 | 2019 | 58 | |
| 16 | 2019 | 29 | |
| 17 | Automatic Accident Detection, Ambulance Rescue and Traffic Signal Controller | 2017 | 2 |
| 18 | 2013 | 0 | |
| 19 | Deterministic and probabilistic models on VLSI cell placement - A survey | 2012 | 1 |
| 20 | Application of Hypergraph in VLSI Cell Partitioning | 2010 | 0 |
About R. Manikandan
R. Manikandan is a scholar working on Health Information Management, Computer Networks and Communications and Artificial Intelligence, having authored 148 papers that have together received 2.2k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (17 papers), COVID-19 diagnosis using AI (15 papers), Brain Tumor Detection and Classification (11 papers), Artificial Intelligence in Healthcare (10 papers), AI in cancer detection (10 papers), Energy Efficient Wireless Sensor Networks (8 papers), Network Security and Intrusion Detection (7 papers) and VLSI and FPGA Design Techniques (7 papers). The work is most often cited by research in Health Informatics (55 citations), Computer Networks and Communications (585 citations) and Health Information Management (115 citations). R. Manikandan has collaborated with scholars based in India, Australia and United States. Frequent co-authors include Jafar A. Alzubi, Amir H. Gandomi, Rizwan Patan, Omar A. Alzubi, Ramesh Sekaran, Deepak Gupta, Ambeshwar Kumar, Ashish Singh, Ashish Khanna and Fadi Al‐Turjman. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Expert Systems with 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.