N. U. Prabhu
- Management Information Systems top 1%
- Management Science and Operations Research top 1%
- Statistics and Probability top 1%
- Mathematical Physics top 5%
- Computer Networks and Communications top 5%
- Co-authors
- A. HuitsonI. V. BasawaYixin ZhuJ. GaniSusan M. PittsAntónio PachecoJ. M. A. TanchocoLoon Ching Tang
- Topics
- Advanced Queuing Theory Analysis (29 papers)Stochastic processes and statistical mechanics (15 papers)Probability and Risk Models (10 papers)
- Cited by
- Management Information SystemsManagement Science and Operations ResearchStatistics and Probability
- Partner nations
- United StatesAustraliaIndia
In The Last Decade
N. U. Prabhu
65 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 85
- Management Information Systems 633
- Management Science and Operations Research 498
- Statistics and Probability 288
- Mathematical Physics 230
- Computer Networks and Communications 178
Countries citing papers authored by N. U. Prabhu
This map shows the geographic impact of N. U. Prabhu'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 N. U. Prabhu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. U. Prabhu more than expected).
Fields of papers citing papers by N. U. Prabhu
This network shows the impact of papers produced by N. U. Prabhu. 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 N. U. Prabhu. The network helps show where N. U. Prabhu may publish in the future.
Co-authorship network of co-authors of N. U. Prabhu
This figure shows the co-authorship network connecting the top 25 collaborators of N. U. Prabhu. A scholar is included among the top collaborators of N. U. Prabhu 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 N. U. Prabhu. N. U. Prabhu 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 | 67 | |
| 4 | 38 | |
| 5 | 10 | |
| 6 | Markov renewal and Markov-additive processes | 2 |
| 7 | Statistical inference from stochastic processes : proceedings of the AMS-IMS-SIAM Joint Summer Research Conference held August 9-15, 1987, with support from the National Science Foundation and the Army Research Office | 1 |
| 8 | 18 | |
| 9 | 1 | |
| 10 | 15 | |
| 11 | 2 | |
| 12 | 2 | |
| 13 | 4 | |
| 14 | 15 | |
| 15 | 9 | |
| 16 | 13 | |
| 17 | 51 | |
| 18 | 30 | |
| 19 | 37 | |
| 20 | 14 |
About N. U. Prabhu
N. U. Prabhu is a scholar working on Management Information Systems, Mathematical Physics and Management Science and Operations Research, having authored 70 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Queuing Theory Analysis (29 papers), Stochastic processes and statistical mechanics (15 papers) and Probability and Risk Models (10 papers). The work is most often cited by research in Management Information Systems (633 citations), Management Science and Operations Research (498 citations) and Statistics and Probability (288 citations). N. U. Prabhu has collaborated with scholars based in United States, Australia and India. Frequent co-authors include A. Huitson, I. V. Basawa, Yixin Zhu, J. Gani, Susan M. Pitts, António Pacheco, J. M. A. Tanchoco, Loon Ching Tang, Michael Rubinovitch and Yan Zhu. Their work appears in journals such as Nature, Journal of the American Statistical Association and Econometrica.
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.