Shashwat Shivam

446 citations
9 papers · 216 indexed · h-index 5
Topics
COVID-19 epidemiological studies (4 papers)SARS-CoV-2 and COVID-19 Research (3 papers)Photovoltaic System Optimization Techniques (3 papers)
Partner nations
United StatesIndiaCanada

In The Last Decade

Shashwat Shivam

9 papers receiving 211 citations

Peers

Shashwat Shivam
Comparison fields: 5 of 78
  • Modeling and Simulation 117
  • Infectious Diseases 86
  • Economics and Econometrics 34
  • Public Health, Environmental and Occupational Health 25
  • Epidemiology 22
Replace Conan Zhao with:
Conan Zhao United States
Sebastián Contreras Chile
Trystan Leng United Kingdom
Jiarui Sun China
Konstantin S. Sharov Russia
Joe Hilton United Kingdom
Viona Ojiambo Kenya
Emma S. Garlock Canada
Francesco Di Lauro United Kingdom
Duncan Kioi Gathungu Kenya
Shashwat Shivam relative to Conan Zhao United States Conan Zhao's profile →
Citations per field
00.5×1.5×
Conan Zhao · 1×
Citations per year

Countries citing papers authored by Shashwat Shivam

Since Specialization
Citations

This map shows the geographic impact of Shashwat Shivam'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 Shashwat Shivam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shashwat Shivam more than expected).

Fields of papers citing papers by Shashwat Shivam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shashwat Shivam. 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 Shashwat Shivam. The network helps show where Shashwat Shivam may publish in the future.

Co-authorship network of co-authors of Shashwat Shivam

This figure shows the co-authorship network connecting the top 25 collaborators of Shashwat Shivam. A scholar is included among the top collaborators of Shashwat Shivam 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 Shashwat Shivam. Shashwat Shivam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 2
2 9
3 1
4 38
5 143
6 10
7 1
8 1
9 11

About Shashwat Shivam

Shashwat Shivam is a scholar working on Modeling and Simulation, Health and Energy Engineering and Power Technology, having authored 9 papers that have together received 216 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (4 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and Photovoltaic System Optimization Techniques (3 papers). The work is most often cited by research in Modeling and Simulation (117 citations), Infectious Diseases (86 citations) and Health (11 citations). Shashwat Shivam has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Joshua S. Weitz, Guanlin Li, Ashley R. Coenen, Jonathan Dushoff, Stephen J. Beckett, Conan Zhao, Chung Yin Leung, Sang Woo Park, Rogelio A. Rodriguez-Gonzalez and David Demory. Their work appears in journals such as Nature Medicine, Vaccine and International Journal of Robust and Nonlinear Control.

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.

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