Saumil Doshi

427 citations
12 papers · 165 · h-index 7

Impact in

    • Influenza Virus Research Studies
    • Respiratory viral infections research
    • Pneumonia and Respiratory Infections
    • COVID-19 epidemiological studies

Papers in

    • Influenza Virus Research Studies 5
    • Respiratory viral infections research 4
    • Antifungal resistance and susceptibility 3
    • Antimicrobial Resistance in Staphylococcus 2

Saumil Doshi

12 papers receiving 160 citations

Peers

Saumil Doshi
Comparison fields: 5 of 55
  • Epidemiology 129
  • Modeling and Simulation 15
  • Infectious Diseases 57
  • Health 5
  • Endocrine and Autonomic Systems 4
Replace Tim Uyeki with:
Tim Uyeki United States
Sierk Marbus Netherlands
Alaina Stoute United States
Ashish Satav India
K. A. Stolyarov Russia
Nicholas Gallagher United States
Endalkachew Belayneh Melese Ethiopia
Mélina Messaoudi France
Ben Waite New Zealand
Nishi Prabdial‐Sing South Africa
Saumil Doshi relative to Tim Uyeki United States Tim Uyeki's profile →
Citations per field
00.5×1.5×2.5×
Tim Uyeki · 1×
Citations per year

Countries citing papers authored by Saumil Doshi

Since Specialization
Citations

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

Fields of papers citing papers by Saumil Doshi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Saumil Doshi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Saumil Doshi Line = papers co-authored together Saumil Doshi links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 201062
2 201131
3 201014
4 201514
5 201512
6 20176
7 20146
8 20125
9 20224
10 20124
11 20244
12 20163

About Saumil Doshi

Saumil Doshi is a scholar working on Epidemiology, Infectious Diseases, Modeling and Simulation, Surgery and Pharmacology, having authored 12 papers that have together received 165 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (5 papers), Respiratory viral infections research (4 papers), Antifungal resistance and susceptibility (3 papers), COVID-19 epidemiological studies (3 papers), Antimicrobial Resistance in Staphylococcus (2 papers), Long-Term Effects of COVID-19 (1 paper), Pharmacological Effects and Toxicity Studies (1 paper) and Pituitary Gland Disorders and Treatments (1 paper). The work is most often cited by research in Epidemiology (129 citations), Modeling and Simulation (15 citations), Infectious Diseases (57 citations), Health (5 citations) and Endocrine and Autonomic Systems (4 citations). Saumil Doshi has collaborated with scholars based in United States, Mongolia and Uganda. Frequent co-authors include Alicia M. Fry, Laurie Kamimoto, Kirsten St. George, Meredith Vandermeer, Samuel B. Graitcer, Janice K. Louie, Alexander Klimov, Jennifer Laplante, Larisa V. Gubareva and Zack Moore. Their work appears in journals such as Clinical Infectious Diseases, Infection Control and Hospital Epidemiology, Influenza and Other Respiratory Viruses, PM&R and Public Health 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.

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