Jennifer McManis

37 total papers · 470 total citations
23 papers, 260 citations indexed

About

Jennifer McManis is a scholar working on Computer Networks and Communications, Sociology and Political Science and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jennifer McManis has authored 23 papers receiving a total of 260 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Networks and Communications, 6 papers in Sociology and Political Science and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jennifer McManis's work include Multimedia Communication and Technology (6 papers), Peer-to-Peer Network Technologies (5 papers) and Caching and Content Delivery (5 papers). Jennifer McManis is often cited by papers focused on Multimedia Communication and Technology (6 papers), Peer-to-Peer Network Technologies (5 papers) and Caching and Content Delivery (5 papers). Jennifer McManis collaborates with scholars based in Ireland, United Kingdom and United States. Jennifer McManis's co-authors include Shen Wang, Soufiene Djahel, Zonghua Zhang, Cristina Hava Muntean, Gabriel‐Miro Muntean, Quang Lê Đăng, Alexandra I. Cristea, Mominul Ahsan, M.S.J. Hashmi and Liam Murphy and has published in prestigious journals such as IEEE Transactions on Vehicular Technology, IEEE Transactions on Intelligent Transportation Systems and Wireless Networks.

In The Last Decade

Jennifer McManis

22 papers receiving 242 citations

Author Peers

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

Author Last Decade Papers Cites
Jennifer McManis 101 99 87 83 78 23 260
Manish Chaturvedi 132 1.3× 116 1.2× 75 0.9× 61 0.7× 58 0.7× 34 304
Wangyang Wei 110 1.1× 51 0.5× 68 0.8× 85 1.0× 131 1.7× 22 320
Sylvain Lecomte 97 1.0× 83 0.8× 53 0.6× 31 0.4× 103 1.3× 26 301
Djamel Khadraoui 62 0.6× 90 0.9× 123 1.4× 109 1.3× 87 1.1× 32 321
Benito Úbeda 55 0.5× 139 1.4× 35 0.4× 34 0.4× 95 1.2× 15 272
Chia-Wei Tseng 73 0.7× 117 1.2× 39 0.4× 38 0.5× 185 2.4× 16 324
Yao-Tsung Yang 73 0.7× 117 1.2× 39 0.4× 35 0.4× 176 2.3× 18 319
David Gundlegård 138 1.4× 64 0.6× 208 2.4× 49 0.6× 41 0.5× 32 312
Joe Palen 93 0.9× 49 0.5× 72 0.8× 106 1.3× 115 1.5× 25 324
Dingyuan Shi 35 0.3× 58 0.6× 33 0.4× 19 0.2× 71 0.9× 20 288

Countries citing papers authored by Jennifer McManis

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer McManis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jennifer McManis

This figure shows the co-authorship network connecting the top 25 collaborators of Jennifer McManis. A scholar is included among the top collaborators of Jennifer McManis 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 Jennifer McManis. Jennifer McManis 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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