Corey M. Peak

34 total papers · 1.4k total citations
13 papers, 669 citations indexed

About

Corey M. Peak is a scholar working on Modeling and Simulation, Infectious Diseases and Epidemiology. According to data from OpenAlex, Corey M. Peak has authored 13 papers receiving a total of 669 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Modeling and Simulation, 5 papers in Infectious Diseases and 5 papers in Epidemiology. Recurrent topics in Corey M. Peak's work include COVID-19 epidemiological studies (6 papers), Influenza Virus Research Studies (3 papers) and Viral Infections and Outbreaks Research (3 papers). Corey M. Peak is often cited by papers focused on COVID-19 epidemiological studies (6 papers), Influenza Virus Research Studies (3 papers) and Viral Infections and Outbreaks Research (3 papers). Corey M. Peak collaborates with scholars based in United States, United Kingdom and Switzerland. Corey M. Peak's co-authors include Caroline O. Buckee, Yonatan H. Grad, Lauren M. Childs, Marc Lipsitch, Rebecca Kahn, Ruoran Li, GM Leung, Joseph T. Wu, Andrew J. Tatem and Erik Wetter and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and Clinical Infectious Diseases.

In The Last Decade

Corey M. Peak

13 papers receiving 646 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Corey M. Peak 342 247 133 106 72 13 669
F. Paul Spitzner 425 1.2× 135 0.5× 120 0.9× 55 0.5× 174 2.4× 9 612
Jonas Dehning 452 1.3× 140 0.6× 128 1.0× 65 0.6× 174 2.4× 10 597
Kaiwei Luo 296 0.9× 220 0.9× 83 0.6× 41 0.4× 45 0.6× 24 605
Spencer J. Fox 485 1.4× 236 1.0× 296 2.2× 101 1.0× 101 1.4× 36 754
Laura Di Domenico 356 1.0× 184 0.7× 131 1.0× 61 0.6× 122 1.7× 16 580
Shu-Wan Jian 328 1.0× 357 1.4× 107 0.8× 48 0.5× 61 0.8× 10 715
Jianbo Yan 173 0.5× 358 1.4× 33 0.2× 47 0.4× 45 0.6× 17 637
Áine B. Collins 502 1.5× 412 1.7× 125 0.9× 74 0.7× 130 1.8× 13 745
Ta-Chou Vincent Ng 330 1.0× 326 1.3× 76 0.6× 26 0.2× 72 1.0× 10 680
Amy Gimma 544 1.6× 193 0.8× 153 1.2× 51 0.5× 208 2.9× 21 787

Countries citing papers authored by Corey M. Peak

Since Specialization
Citations

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

Fields of papers citing papers by Corey M. Peak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Corey M. Peak. 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 Corey M. Peak. The network helps show where Corey M. Peak may publish in the future.

Co-authorship network of co-authors of Corey M. Peak

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

All Works

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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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