Prabhat Ranjan Singh
- Computer Networks and Communications top 10%
- Information Systems top 5%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Computational Theory and Mathematics top 10%
- Co-authors
- Rahul YadavMohamed Abd ElazizShengwu XiongWeizhe ZhangOmprakash KaiwartyaIbrahim A. ElgendyYu‐Chu TianVivek Kumar Singh
- Topics
- Metaheuristic Optimization Algorithms Research (3 papers)IoT and Edge/Fog Computing (2 papers)Aesthetic Perception and Analysis (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Access
In The Last Decade
Prabhat Ranjan Singh
12 papers receiving 292 citations
Peers
Comparison fields: 5 of 57
- Computer Networks and Communications 138
- Information Systems 117
- Artificial Intelligence 92
- Electrical and Electronic Engineering 64
- Computational Theory and Mathematics 42
Countries citing papers authored by Prabhat Ranjan Singh
This map shows the geographic impact of Prabhat Ranjan Singh'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 Prabhat Ranjan Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prabhat Ranjan Singh more than expected).
Fields of papers citing papers by Prabhat Ranjan Singh
This network shows the impact of papers produced by Prabhat Ranjan Singh. 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 Prabhat Ranjan Singh. The network helps show where Prabhat Ranjan Singh may publish in the future.
Co-authorship network of co-authors of Prabhat Ranjan Singh
This figure shows the co-authorship network connecting the top 25 collaborators of Prabhat Ranjan Singh. A scholar is included among the top collaborators of Prabhat Ranjan Singh 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 Prabhat Ranjan Singh. Prabhat Ranjan Singh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 19 | |
| 2 | 9 | |
| 3 | 39 | |
| 4 | 3 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | 34 | |
| 8 | 43 | |
| 9 | 130 | |
| 10 | 11 | |
| 11 | 8 | |
| 12 | 4 |
About Prabhat Ranjan Singh
Prabhat Ranjan Singh is a scholar working on Hardware and Architecture, Museology and Computer Graphics and Computer-Aided Design, having authored 12 papers that have together received 306 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (3 papers), IoT and Edge/Fog Computing (2 papers) and Aesthetic Perception and Analysis (2 papers). The work is most often cited by research in Computer Networks and Communications (138 citations), Information Systems (117 citations) and Artificial Intelligence (92 citations). Prabhat Ranjan Singh has collaborated with scholars based in China, India and Egypt. Frequent co-authors include Rahul Yadav, Mohamed Abd Elaziz, Shengwu Xiong, Weizhe Zhang, Omprakash Kaiwartya, Ibrahim A. Elgendy, Yu‐Chu Tian, Vivek Kumar Singh, Tanesh Kumar and Teerath Das. Their work appears in journals such as SHILAP Revista de lepidopterología, 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.