Pramod K. Varshney
- Computer Networks and Communications top 5%
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Computational Mechanics
- Co-authors
- Ruixin NiuHao ChenBiao ChenBhavya KailkhuraSwastik BrahmaPriyadip RayRamachandran VaidyanathanMarimuthu Palaniswami
- Topics
- Distributed Sensor Networks and Detection Algorithms (8 papers)Target Tracking and Data Fusion in Sensor Networks (7 papers)Indoor and Outdoor Localization Technologies (2 papers)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Pramod K. Varshney
10 papers receiving 320 citations
Peers
Comparison fields: 5 of 36
- Computer Networks and Communications 279
- Artificial Intelligence 231
- Electrical and Electronic Engineering 131
- Control and Systems Engineering 42
- Computational Mechanics 28
Countries citing papers authored by Pramod K. Varshney
This map shows the geographic impact of Pramod K. Varshney'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 Pramod K. Varshney with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pramod K. Varshney more than expected).
Fields of papers citing papers by Pramod K. Varshney
This network shows the impact of papers produced by Pramod K. Varshney. 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 Pramod K. Varshney. The network helps show where Pramod K. Varshney may publish in the future.
Co-authorship network of co-authors of Pramod K. Varshney
This figure shows the co-authorship network connecting the top 25 collaborators of Pramod K. Varshney. A scholar is included among the top collaborators of Pramod K. Varshney 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 Pramod K. Varshney. Pramod K. Varshney 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 | 5 | |
| 3 | 10 | |
| 4 | 4 | |
| 5 | 38 | |
| 6 | 67 | |
| 7 | 2 | |
| 8 | 4 | |
| 9 | 10 | |
| 10 | 190 | |
| 11 | 2 |
About Pramod K. Varshney
Pramod K. Varshney is a scholar working on Computer Networks and Communications, Artificial Intelligence and Statistics and Probability, having authored 11 papers that have together received 332 indexed citations. Recurring topics across this work include Distributed Sensor Networks and Detection Algorithms (8 papers), Target Tracking and Data Fusion in Sensor Networks (7 papers) and Indoor and Outdoor Localization Technologies (2 papers). The work is most often cited by research in Computer Networks and Communications (279 citations), Artificial Intelligence (231 citations) and Statistics and Probability (27 citations). Pramod K. Varshney has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Ruixin Niu, Hao Chen, Biao Chen, Bhavya Kailkhura, Swastik Brahma, Priyadip Ray, Ramachandran Vaidyanathan, Marimuthu Palaniswami, Xueqian Wang and C. Hartmann. Their work appears in journals such as IEEE Transactions on Signal Processing, Signal Processing and Information Processing Letters.
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.