Srinivasan Venkatramanan
- Modeling and Simulation top 0.2%
- Infectious Diseases top 5%
- Economics and Econometrics top 5%
- Epidemiology
- Public Health, Environmental and Occupational Health top 10%
- Co-authors
- Madhav MaratheBryan LewisStephen EubankChristopher L. BarrettIrene EckstrandAnil VullikantiJiangzhuo ChenAniruddha Adiga
- Topics
- COVID-19 epidemiological studies (28 papers)Data-Driven Disease Surveillance (17 papers)Complex Network Analysis Techniques (12 papers)
- Partner nations
- United StatesIndiaHong Kong
In The Last Decade
Srinivasan Venkatramanan
43 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Modeling and Simulation 846
- Infectious Diseases 385
- Economics and Econometrics 325
- Epidemiology 248
- Public Health, Environmental and Occupational Health 140
Countries citing papers authored by Srinivasan Venkatramanan
This map shows the geographic impact of Srinivasan Venkatramanan'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 Srinivasan Venkatramanan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Srinivasan Venkatramanan more than expected).
Fields of papers citing papers by Srinivasan Venkatramanan
This network shows the impact of papers produced by Srinivasan Venkatramanan. 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 Srinivasan Venkatramanan. The network helps show where Srinivasan Venkatramanan may publish in the future.
Co-authorship network of co-authors of Srinivasan Venkatramanan
This figure shows the co-authorship network connecting the top 25 collaborators of Srinivasan Venkatramanan. A scholar is included among the top collaborators of Srinivasan Venkatramanan 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 Srinivasan Venkatramanan. Srinivasan Venkatramanan 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 | 2 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 10 | |
| 6 | 6 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 47 | |
| 11 | 5 | |
| 12 | Commentary on Ferguson, et al., “Impact of Non-pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand”breakdown → | 718 |
| 13 | 5 | |
| 14 | 30 | |
| 15 | 116 | |
| 16 | 12 | |
| 17 | 33 | |
| 18 | 33 | |
| 19 | 118 | |
| 20 | 10 |
About Srinivasan Venkatramanan
Srinivasan Venkatramanan is a scholar working on Modeling and Simulation, Statistical and Nonlinear Physics and Transportation, having authored 46 papers that have together received 1.4k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (28 papers), Data-Driven Disease Surveillance (17 papers) and Complex Network Analysis Techniques (12 papers). The work is most often cited by research in Modeling and Simulation (846 citations), Infectious Diseases (385 citations) and Economics and Econometrics (325 citations). Srinivasan Venkatramanan has collaborated with scholars based in United States, India and Hong Kong. Frequent co-authors include Madhav Marathe, Bryan Lewis, Stephen Eubank, Christopher L. Barrett, Irene Eckstrand, Anil Vullikanti, Jiangzhuo Chen, Aniruddha Adiga, Dave Higdon and Devdatt Dubhashi. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Scientific Reports.
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.