Evan L Ray

2.9k citations
17 papers · 664 · 1 hit paper · h-index 8

Impact in

Papers in

Evan L Ray

16 papers receiving 652 citations

Evan L Ray's Hit Papers

Evaluating epidemic forecasts in an interval format 2021 · 137 citations
1370+1+3Years since publication4080120

Peers

Evan L Ray
Comparison fields: 5 of 93
  • Modeling and Simulation 345
  • Epidemiology 268
  • Infectious Diseases 74
  • Management Science and Operations Research 52
  • Public Health, Environmental and Occupational Health 90
Replace Dave Osthus with:
Dave Osthus United States
Logan Brooks United States
Spencer J. Fox United States
Alexander Kirpich United States
Kimberlyn Roosa United States
Johannes Bracher Germany
Paul Birrell United Kingdom
Chong You China
Evan Moore United States
Nicholas Generous United States
Evan L Ray relative to Dave Osthus United States Dave Osthus's profile →
Citations per field
00.5×1.5×2.3×
Dave Osthus · 1×
Citations per year

Countries citing papers authored by Evan L Ray

Since Specialization
Citations

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

Fields of papers citing papers by Evan L Ray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Evan L Ray. 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 Evan L Ray. The network helps show where Evan L Ray may publish in the future.

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 2019154
2
Evaluating epidemic forecasts in an interval format
Hit paper breakdown →
2021137
3 2019102
4 201885
5 201851
6 201741
7 201436
8 202227
9 20186
10 20185
11 20194
12 20244
13 20244
14 20054
15 20212
16 20232
17 20240

About Evan L Ray

Evan L Ray is a scholar working on Modeling and Simulation, Epidemiology, Artificial Intelligence, Management Science and Operations Research and Genetics, having authored 17 papers that have together received 664 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (10 papers), Data-Driven Disease Surveillance (8 papers), Influenza Virus Research Studies (6 papers), Agricultural risk and resilience (2 papers), Climate variability and models (2 papers), Forecasting Techniques and Applications (2 papers), Genetic and phenotypic traits in livestock (2 papers) and Genetic Associations and Epidemiology (2 papers). The work is most often cited by research in Modeling and Simulation (345 citations), Epidemiology (268 citations), Infectious Diseases (74 citations), Management Science and Operations Research (52 citations) and Public Health, Environmental and Occupational Health (90 citations). Evan L Ray has collaborated with scholars based in United States, Germany and Thailand. Frequent co-authors include Nicholas G Reich, Johannes Bracher, Tilmann Gneiting, Michael A. Johansson, Matthew Biggerstaff, Logan Brooks, Jeffrey Shaman, Teresa K. Yamana, Sasikiran Kandula and Abhinav Tushar. Their work appears in journals such as PLoS Computational Biology, Statistics in Medicine, Proceedings of the National Academy of Sciences, Epidemics and International Journal of Forecasting.

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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