Evan L Ray

2.8k total citations · 1 hit paper
17 papers, 623 citations indexed

About

Evan L Ray is a scholar working on Modeling and Simulation, Epidemiology and Artificial Intelligence. According to data from OpenAlex, Evan L Ray has authored 17 papers receiving a total of 623 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Modeling and Simulation, 9 papers in Epidemiology and 2 papers in Artificial Intelligence. Recurrent topics in Evan L Ray's work include COVID-19 epidemiological studies (10 papers), Data-Driven Disease Surveillance (8 papers) and Influenza Virus Research Studies (6 papers). Evan L Ray is often cited by papers focused on COVID-19 epidemiological studies (10 papers), Data-Driven Disease Surveillance (8 papers) and Influenza Virus Research Studies (6 papers). Evan L Ray collaborates with scholars based in United States, Germany and Brazil. Evan L Ray's co-authors include Nicholas G Reich, Johannes Bracher, Tilmann Gneiting, Michael A. Johansson, Logan Brooks, Matthew Biggerstaff, Craig McGowan, Roni Rosenfeld, Jeffrey Shaman and Evan Moore and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Biometrics and Emerging infectious diseases.

In The Last Decade

Evan L Ray

16 papers receiving 610 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Evaluating epidemic forecasts in an interval format

2021 126 citations Johannes Bracher, Evan L Ray et al. PLoS Computational Biology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Evan L Ray United States	8	360	287	108	84	78	17	623
Dave Osthus United States	12	346 1.0×	288 1.0×	85 0.8×	89 1.1×	66 0.8×	33	654
Logan Brooks United States	9	333 0.9×	315 1.1×	56 0.5×	67 0.8×	54 0.7×	12	524
Alexander Kirpich United States	11	431 1.2×	104 0.4×	82 0.8×	154 1.8×	123 1.6×	34	891
Spencer J. Fox United States	14	492 1.4×	303 1.1×	102 0.9×	236 2.8×	38 0.5×	37	764
Geoffrey Fairchild United States	12	189 0.5×	305 1.1×	156 1.4×	104 1.2×	76 1.0×	29	681
Alberto Aleta Spain	16	755 2.1×	255 0.9×	134 1.2×	236 2.8×	51 0.7×	34	1.2k
Nicholas Generous United States	13	180 0.5×	285 1.0×	99 0.9×	71 0.8×	51 0.7×	26	536
Teresa K. Yamana United States	13	400 1.1×	260 0.9×	258 2.4×	206 2.5×	50 0.6×	23	847
Robert Moss Australia	17	227 0.6×	242 0.8×	53 0.5×	98 1.2×	21 0.3×	35	597
Marie Varughese Canada	8	346 1.0×	100 0.3×	76 0.7×	172 2.0×	30 0.4×	15	523

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-authorship network of co-authors of Evan L Ray

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

All Works

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17 of 17 papers shown

Ray, Evan L, Yijin Wang, Russell D. Wolfinger, & Nicholas G Reich. (2024). Flusion: Integrating multiple data sources for accurate influenza predictions. Epidemics. 50. 100810–100810. 2 indexed citations

Fox, Spencer J., et al.. (2024). Optimizing Disease Outbreak Forecast Ensembles. Emerging infectious diseases. 30(9). 1967–1969. 2 indexed citations

Gerding, Aaron, et al.. (2024). Evaluating infectious disease forecasts with allocation scoring rules. Journal of the Royal Statistical Society Series A (Statistics in Society). 188(4). 1299–1325.

Reich, Nicholas G, et al.. (2023). Assessing the utility of COVID-19 case reports as a leading indicator for hospitalization forecasting in the United States. Epidemics. 45. 100728–100728. 2 indexed citations

Ray, Evan L, Logan Brooks, Jacob Bien, et al.. (2022). Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States. International Journal of Forecasting. 39(3). 1366–1383. 21 indexed citations

Bracher, Johannes, Evan L Ray, Tilmann Gneiting, & Nicholas G Reich. (2021). Evaluating epidemic forecasts in an interval format. PLoS Computational Biology. 17(2). e1008618–e1008618. 126 indexed citations breakdown →

Reich, Nicholas G, et al.. (2021). The Zoltar forecast archive, a tool to standardize and store interdisciplinary prediction research. Scientific Data. 8(1). 59–59. 2 indexed citations

Reich, Nicholas G, Craig McGowan, Teresa K. Yamana, et al.. (2019). Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S.. PLoS Computational Biology. 15(11). e1007486–e1007486. 95 indexed citations

Reich, Nicholas G, Logan Brooks, Spencer J. Fox, et al.. (2019). A collaborative multiyear, multimodel assessment of seasonal influenza forecasting in the United States. Proceedings of the National Academy of Sciences. 116(8). 3146–3154. 145 indexed citations

10.

Ray, Evan L, et al.. (2019). Stochastic imputation for integrated transcriptome association analysis of a longitudinally measured trait. Statistical Methods in Medical Research. 29(4). 1167–1180. 4 indexed citations

11.

Qian, Jing, et al.. (2018). A likelihood‐based approach to transcriptome association analysis. Statistics in Medicine. 38(8). 1357–1373. 6 indexed citations

12.

Lauer, Stephen A., Krzysztof Sakrejda, Evan L Ray, et al.. (2018). Prospective forecasts of annual dengue hemorrhagic fever incidence in Thailand, 2010–2014. Proceedings of the National Academy of Sciences. 115(10). E2175–E2182. 50 indexed citations

13.

Ray, Evan L & Nicholas G Reich. (2018). Prediction of infectious disease epidemics via weighted density ensembles. PLoS Computational Biology. 14(2). e1005910–e1005910. 83 indexed citations

14.

Ray, Evan L, Jeffer Eidi Sasaki, Patty S. Freedson, & John Staudenmayer. (2018). Physical Activity Classification with Dynamic Discriminative Methods. Biometrics. 74(4). 1502–1511. 5 indexed citations

15.

Ray, Evan L, Krzysztof Sakrejda, Stephen A. Lauer, Michael A. Johansson, & Nicholas G Reich. (2017). Infectious disease prediction with kernel conditional density estimation. Statistics in Medicine. 36(30). 4908–4929. 40 indexed citations

16.

Keadle, Sarah Kozey, Kate Lyden, Amanda Hickey, et al.. (2014). Validation of a previous day recall for measuring the location and purpose of active and sedentary behaviors compared to direct observation. International Journal of Behavioral Nutrition and Physical Activity. 11(1). 12–12. 36 indexed citations

17.

Ray, Evan L, et al.. (2005). Extending record and playback technologies to support cooperative learning. 669–674. 4 indexed citations

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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