Robert Moss

967 citations
36 papers · 632 · h-index 17

Impact in

    • COVID-19 epidemiological studies
  • Epidemiology top 10%
    • Influenza Virus Research Studies
    • Data-Driven Disease Surveillance
    • Respiratory viral infections research

Papers in

Robert Moss

35 papers receiving 612 citations

Peers

Robert Moss
Comparison fields: 5 of 103
  • Modeling and Simulation 208
  • Epidemiology 235
  • Nephrology 32
  • Health 37
  • Infectious Diseases 81
Replace Christina M. Astley with:
Christina M. Astley United States
Eva L. H. Tsui Hong Kong
Dan Xiao China
Matthew Tudball United Kingdom
Sen Ye China
Huipeng Ge China
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Citations per field
00.5×6.4×
Christina M. Astley · 1×
Citations per year

Countries citing papers authored by Robert Moss

Since Specialization
Citations

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

Fields of papers citing papers by Robert Moss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Robert Moss, 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 Robert Moss Line = papers co-authored together Robert Moss links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202061
2 201950
3 202048
4 201546
5 202031
6 201629
7 201227
8 202026
9 201924
10 201122
11 201621
12 201321
13 201120
14 201220
15 201419
16 201919
17 201718
18 201713
19 202013
20 201612

About Robert Moss

Robert Moss is a scholar working on Epidemiology, Modeling and Simulation, Infectious Diseases, Molecular Biology and Nephrology, having authored 36 papers that have together received 632 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (16 papers), COVID-19 epidemiological studies (13 papers), Data-Driven Disease Surveillance (9 papers), Viral Infections and Outbreaks Research (3 papers), Renal function and acid-base balance (3 papers), Advanced Thermodynamics and Statistical Mechanics (2 papers), Ion Transport and Channel Regulation (2 papers) and Electrolyte and hormonal disorders (2 papers). The work is most often cited by research in Modeling and Simulation (208 citations), Epidemiology (235 citations), Nephrology (32 citations), Health (37 citations) and Infectious Diseases (81 citations). Robert Moss has collaborated with scholars based in Australia, United States and France. Frequent co-authors include James M. McCaw, Jodie McVernon, Alexander E. Zarebski, Peter Dawson, Sophie Thomas, Freya M. Shearer, Joshua V. Ross, Nicholas Geard, Anita T. Layton and Haoqi Sun. Their work appears in journals such as Influenza and Other Respiratory Viruses, Epidemics, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, PLoS Computational Biology and American Journal of Physiology-Renal Physiology.

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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