Daniel J. Elson

585 citations
46 papers · 444 · h-index 11

Impact in

Papers in

Daniel J. Elson

43 papers receiving 417 citations

Peers

Daniel J. Elson
Comparison fields: 5 of 13
  • Electrical and Electronic Engineering 400
  • Computer Networks and Communications 36
  • Atomic and Molecular Physics, and Optics 18
  • Ceramics and Composites 3
  • Artificial Intelligence 12
Replace Salah Ibrahim with:
Salah Ibrahim Japan
Sy Dat Le France
Robert Emmerich Germany
Ivan Fernandez de Jauregui Ruiz France
Yequn Zhang United States
Shize Zhang Netherlands
Rafael Rios-Müller France
Marco A. Fernandes Portugal
Joseph E. Berthold United States
L. Rau United States
Daniel J. Elson relative to Salah Ibrahim Japan Salah Ibrahim's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniel J. Elson

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Elson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Elson. 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 Daniel J. Elson. The network helps show where Daniel J. Elson may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201779
2 201876
3 201726
4 201824
5 202324
6 201822
7 201819
8 202316
9 201515
10 201815
11 201714
12 202411
13 202110
14 20179
15 20178
16 20176
17 20236
18 20246
19 20235
20 20245

About Daniel J. Elson

Daniel J. Elson is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Artificial Intelligence, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 46 papers that have together received 444 indexed citations. Recurring topics across this work include Optical Network Technologies (41 papers), Advanced Optical Network Technologies (3 papers), Error Correcting Code Techniques (2 papers), Advanced Photonic Communication Systems (2 papers), Advanced Wireless Communication Techniques (2 papers), Ultra-Wideband Communications Technology (1 paper), Interconnection Networks and Systems (1 paper) and Natural Language Processing Techniques (1 paper). The work is most often cited by research in Electrical and Electronic Engineering (400 citations), Computer Networks and Communications (36 citations), Atomic and Molecular Physics, and Optics (18 citations), Ceramics and Composites (3 citations) and Artificial Intelligence (12 citations). Daniel J. Elson has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Polina Bayvel, Lídia Galdino, Robert I. Killey, Benn Charles Thomsen, Domaniç Lavery, Gabriel Saavedra, Daniel Semrau, Kai Shi, Noboru Yoshikane and Yuta Wakayama. Their work appears in journals such as Journal of Lightwave Technology, Optics Letters, IEEE Photonics Technology Letters, IEEE Access and Optics Express.

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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