Sabuzima Nayak
- Computer Networks and Communications top 10%
- Artificial Intelligence
- Electrical and Electronic Engineering
- Information Systems top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Ripon PatgiriArif AhmedAnupam BiswasSamir KumarNaresh Babu MuppalaneniBirendra BiswalVivek Kadiyala
- Topics
- Caching and Content Delivery (12 papers)IoT and Edge/Fog Computing (7 papers)Internet Traffic Analysis and Secure E-voting (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessInformation Sciences
In The Last Decade
Sabuzima Nayak
22 papers receiving 251 citations
Peers
Comparison fields: 5 of 47
- Computer Networks and Communications 158
- Artificial Intelligence 80
- Electrical and Electronic Engineering 72
- Information Systems 51
- Computer Vision and Pattern Recognition 30
Countries citing papers authored by Sabuzima Nayak
This map shows the geographic impact of Sabuzima Nayak'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 Sabuzima Nayak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sabuzima Nayak more than expected).
Fields of papers citing papers by Sabuzima Nayak
This network shows the impact of papers produced by Sabuzima Nayak. 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 Sabuzima Nayak. The network helps show where Sabuzima Nayak may publish in the future.
Co-authorship network of co-authors of Sabuzima Nayak
This figure shows the co-authorship network connecting the top 25 collaborators of Sabuzima Nayak. A scholar is included among the top collaborators of Sabuzima Nayak 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 Sabuzima Nayak. Sabuzima Nayak 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 | 20 | |
| 3 | 5 | |
| 4 | 32 | |
| 5 | 1 | |
| 6 | 62 | |
| 7 | 15 | |
| 8 | 9 | |
| 9 | 6G: Envisioning the Key Issues and Challenges | 4 |
| 10 | 22 | |
| 11 | 8 | |
| 12 | 18 | |
| 13 | 10 | |
| 14 | 1 | |
| 15 | 5 | |
| 16 | 3 | |
| 17 | 19 | |
| 18 | Machine Learning for Big Data Processing: A Literature Review | 6 |
| 19 | 2 | |
| 20 | 13 |
About Sabuzima Nayak
Sabuzima Nayak is a scholar working on Computer Networks and Communications, Hardware and Architecture and Artificial Intelligence, having authored 22 papers that have together received 262 indexed citations. Recurring topics across this work include Caching and Content Delivery (12 papers), IoT and Edge/Fog Computing (7 papers) and Internet Traffic Analysis and Secure E-voting (6 papers). The work is most often cited by research in Computer Networks and Communications (158 citations), Health Informatics (5 citations) and Signal Processing (29 citations). Sabuzima Nayak has collaborated with scholars based in India, Sweden and Ethiopia. Frequent co-authors include Ripon Patgiri, Arif Ahmed, Anupam Biswas, Samir Kumar, Naresh Babu Muppalaneni, Birendra Biswal and Vivek Kadiyala. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Information Sciences.
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.