Gokul Yenduri
- Artificial Intelligence top 2%
- Computer Networks and Communications top 2%
- Information Systems top 2%
- Human-Computer Interaction top 1%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Thippa Reddy GadekalluPraveen Kumar Reddy MaddikuntaThien Huynh‐TheQuoc‐Viet PhamSweta BhattacharyaWeizheng WangMadhusanka LiyanageDaniel Benevides da Costa
- Topics
- IoT and Edge/Fog Computing (9 papers)Software Engineering Research (7 papers)Blockchain Technology Applications and Security (7 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsIEEE Access
In The Last Decade
Gokul Yenduri
34 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Artificial Intelligence 514
- Computer Networks and Communications 442
- Information Systems 379
- Human-Computer Interaction 270
- Computer Vision and Pattern Recognition 136
Countries citing papers authored by Gokul Yenduri
This map shows the geographic impact of Gokul Yenduri'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 Gokul Yenduri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gokul Yenduri more than expected).
Fields of papers citing papers by Gokul Yenduri
This network shows the impact of papers produced by Gokul Yenduri. 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 Gokul Yenduri. The network helps show where Gokul Yenduri may publish in the future.
Co-authorship network of co-authors of Gokul Yenduri
This figure shows the co-authorship network connecting the top 25 collaborators of Gokul Yenduri. A scholar is included among the top collaborators of Gokul Yenduri 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 Gokul Yenduri. Gokul Yenduri 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 | 9 | |
| 3 | 7 | |
| 4 | 0 | |
| 5 | 7 | |
| 6 | Metaverse for Healthcare: A Survey on Potential Applications, Challenges and Future Directionsbreakdown → | 240 |
| 7 | 6 | |
| 8 | 62 | |
| 9 | 5 | |
| 10 | 7 | |
| 11 | 41 | |
| 12 | 0 | |
| 13 | 3 | |
| 14 | Blockchain for the metaverse: A Reviewbreakdown → | 404 |
| 15 | 2 | |
| 16 | 93 | |
| 17 | 54 | |
| 18 | Federated Learning for intrusion detection system: Concepts, challenges and future directionsbreakdown → | 223 |
| 19 | 10 | |
| 20 | 14 |
About Gokul Yenduri
Gokul Yenduri is a scholar working on Health Informatics, Software and Computer Science Applications, having authored 38 papers that have together received 1.5k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (9 papers), Software Engineering Research (7 papers) and Blockchain Technology Applications and Security (7 papers). The work is most often cited by research in Health Informatics (104 citations), Human-Computer Interaction (270 citations) and Computer Networks and Communications (442 citations). Gokul Yenduri has collaborated with scholars based in India, Lebanon and China. Frequent co-authors include Thippa Reddy Gadekallu, Praveen Kumar Reddy Maddikunta, Thien Huynh‐The, Quoc‐Viet Pham, Sweta Bhattacharya, Weizheng Wang, Madhusanka Liyanage, Daniel Benevides da Costa, Pasika Ranaweera and Rutvij H. Jhaveri. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports 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.