Usha Nandini Raghavan
- Statistical and Nonlinear Physics top 0.2%
- Artificial Intelligence top 2%
- Computer Networks and Communications top 2%
- Strategy and Management top 5%
- Molecular Biology
- Co-authors
- Soundar KumaraRéka AlbertMark GreavesAmit SuranaChristopher S. HallChristoph WaldPuneet BhargavaSang‐Gook Kim
- Topics
- Healthcare Policy and Management (3 papers)Healthcare Operations and Scheduling Optimization (3 papers)Complex Network Analysis Techniques (3 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputer Networks and CommunicationsManagement Information Systems
- Journals
- American Journal of RoentgenologyInternational Journal of Production ResearchIEEE Intelligent Systems
- Partner nations
- United StatesFinland
In The Last Decade
Usha Nandini Raghavan
11 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Statistical and Nonlinear Physics 1.7k
- Artificial Intelligence 778
- Computer Networks and Communications 598
- Strategy and Management 371
- Molecular Biology 295
Countries citing papers authored by Usha Nandini Raghavan
This map shows the geographic impact of Usha Nandini Raghavan'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 Usha Nandini Raghavan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Usha Nandini Raghavan more than expected).
Fields of papers citing papers by Usha Nandini Raghavan
This network shows the impact of papers produced by Usha Nandini Raghavan. 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 Usha Nandini Raghavan. The network helps show where Usha Nandini Raghavan may publish in the future.
Co-authorship network of co-authors of Usha Nandini Raghavan
This figure shows the co-authorship network connecting the top 25 collaborators of Usha Nandini Raghavan. A scholar is included among the top collaborators of Usha Nandini Raghavan 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 Usha Nandini Raghavan. Usha Nandini Raghavan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 8 | |
| 3 | 1 | |
| 4 | 31 | |
| 5 | 15 | |
| 6 | 4 | |
| 7 | Near linear time algorithm to detect community structures in large-scale networksbreakdown → | 2167 |
| 8 | 14 | |
| 9 | 18 | |
| 10 | 421 | |
| 11 | 154 |
About Usha Nandini Raghavan
Usha Nandini Raghavan is a scholar working on Emergency Medical Services, Emergency Medicine and Statistical and Nonlinear Physics, having authored 11 papers that have together received 2.8k indexed citations. Recurring topics across this work include Healthcare Policy and Management (3 papers), Healthcare Operations and Scheduling Optimization (3 papers) and Complex Network Analysis Techniques (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.7k citations), Computer Networks and Communications (598 citations) and Management Information Systems (227 citations). Usha Nandini Raghavan has collaborated with scholars based in United States and Finland. Frequent co-authors include Soundar Kumara, Réka Albert, Mark Greaves, Amit Surana, Christopher S. Hall, Christoph Wald, Puneet Bhargava, Sang‐Gook Kim, Xiang Zhang and Brady J. McKee. Their work appears in journals such as American Journal of Roentgenology, International Journal of Production Research and IEEE Intelligent Systems.
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.