David G. Daut

104 total papers · 1.7k total citations
76 papers, 1.2k citations indexed

About

David G. Daut is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, David G. Daut has authored 76 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Electrical and Electronic Engineering, 36 papers in Computer Vision and Pattern Recognition and 27 papers in Computer Networks and Communications. Recurrent topics in David G. Daut's work include Advanced Wireless Communication Techniques (25 papers), Advanced Data Compression Techniques (23 papers) and Wireless Communication Networks Research (14 papers). David G. Daut is often cited by papers focused on Advanced Wireless Communication Techniques (25 papers), Advanced Data Compression Techniques (23 papers) and Wireless Communication Networks Research (14 papers). David G. Daut collaborates with scholars based in United States, Taiwan and Germany. David G. Daut's co-authors include J.W. Modestino, Aly F. Elrefaie, Wen‐Yang Gao, D.A. Atlas, Richard E. Wagner, Wen Gao, Dongming Zhao, L.J. Greenstein, M. Shridhar and Ming Yu and has published in prestigious journals such as IEEE Transactions on Information Theory, Optics Letters and IEEE Transactions on Communications.

In The Last Decade

David G. Daut

66 papers receiving 1.1k citations

Author Peers

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

Author Last Decade Papers Cites
David G. Daut 697 506 287 247 144 76 1.2k
Nazanin Rahnavard 876 1.3× 985 1.9× 218 0.8× 170 0.7× 306 2.1× 91 1.5k
Jienan Chen 642 0.9× 483 1.0× 182 0.6× 78 0.3× 152 1.1× 91 1.2k
Yukihiro Tadokoro 511 0.7× 172 0.3× 145 0.5× 295 1.2× 85 0.6× 143 1.1k
Nicola Laurenti 704 1.0× 472 0.9× 266 0.9× 151 0.6× 326 2.3× 90 1.2k
Daniel Roviras 975 1.4× 524 1.0× 163 0.6× 94 0.4× 102 0.7× 115 1.4k
See-May Phoong 938 1.3× 422 0.8× 445 1.6× 429 1.7× 69 0.5× 109 1.4k
Don Torrieri 898 1.3× 913 1.8× 63 0.2× 226 0.9× 165 1.1× 116 1.5k
Chamith Wijenayake 293 0.4× 635 1.3× 245 0.9× 507 2.1× 558 3.9× 78 1.3k
R. David Koilpillai 716 1.0× 204 0.4× 377 1.3× 563 2.3× 24 0.2× 94 1.1k
N. Felber 827 1.2× 556 1.1× 153 0.5× 78 0.3× 276 1.9× 62 1.3k

Countries citing papers authored by David G. Daut

Since Specialization
Citations

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

Fields of papers citing papers by David G. Daut

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David G. Daut. 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 David G. Daut. The network helps show where David G. Daut may publish in the future.

Co-authorship network of co-authors of David G. Daut

This figure shows the co-authorship network connecting the top 25 collaborators of David G. Daut. A scholar is included among the top collaborators of David G. Daut 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 David G. Daut. David G. Daut 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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