Eric McDermid

416 citations
13 papers · 145 indexed · h-index 7

Impact in

Papers in

Eric McDermid

13 papers receiving 138 citations

Peers

Eric McDermid
Comparison fields: 5 of 41
  • Management Science and Operations Research 73
  • Computational Theory and Mathematics 69
  • Economics and Econometrics 106
  • Computer Networks and Communications 23
  • Transplantation 2
Replace Argyrios Deligkas with:
Argyrios Deligkas United Kingdom
Katarzyna Paluch Poland
Saeed Seddighin United States
Ayumi Igarashi Japan
Holger Spakowski Germany
Umang Bhaskar United States
Ruta Mehta United States
John Fearnley United Kingdom
Ildikó Schlotter Hungary
Norbert Jobst United Kingdom
Eric McDermid relative to Argyrios Deligkas United Kingdom Argyrios Deligkas's profile →
Citations per field
00.5×5.5×
Argyrios Deligkas · 1×
Citations per year

Countries citing papers authored by Eric McDermid

Since Specialization
Citations

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

Fields of papers citing papers by Eric McDermid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 7 scholars most cited alongside Eric McDermid, 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 Eric McDermid Line = papers co-authored together Eric McDermid links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 20155
2 20142
3 20144
4 20132
5 20133
6 201212
7 20128
8 201116
9 201014
10 20104
11 200933
12 200933
13 20089

About Eric McDermid

Eric McDermid is a scholar working on Computational Theory and Mathematics, Economics and Econometrics, Management Science and Operations Research, Computer Networks and Communications and Industrial and Manufacturing Engineering, having authored 13 papers that have together received 145 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (9 papers), Game Theory and Voting Systems (8 papers), Advanced Graph Theory Research (4 papers), Optimization and Search Problems (2 papers), Logic, Reasoning, and Knowledge (2 papers), Interconnection Networks and Systems (1 paper), Game Theory and Applications (1 paper) and Scheduling and Optimization Algorithms (1 paper). The work is most often cited by research in Management Science and Operations Research (73 citations), Computational Theory and Mathematics (69 citations), Economics and Econometrics (106 citations), Computer Networks and Communications (23 citations) and Transplantation (2 citations). Eric McDermid has collaborated with scholars based in United Kingdom, United States and Hungary. Frequent co-authors include Péter Bíró, David F. Manlove, Robert W. Irving, Christine T. Cheng, I. Suzuki, Yuan Qu and Keith Edwards. Their work appears in journals such as Algorithmica, Discrete Applied Mathematics, Theoretical Computer Science, Journal of Combinatorial Optimization and Algorithms.

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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