Jae C. Oh

419 citations
51 papers · 211 · h-index 7

Impact in

Papers in

Jae C. Oh

47 papers receiving 200 citations

Peers

Jae C. Oh
Comparison fields: 5 of 50
  • Hardware and Architecture 35
  • Computer Networks and Communications 82
  • Statistical and Nonlinear Physics 39
  • Management Science and Operations Research 32
  • Computer Science Applications 10
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Anna Philippou Cyprus
Mohamed Ahmed Canada
Subhashis Majumder India
Xuying Meng China
John P. Rula United States
Miguel A. Mosteiro United States
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Citations per year

Countries citing papers authored by Jae C. Oh

Since Specialization
Citations

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

Fields of papers citing papers by Jae C. Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jae C. Oh. 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 Jae C. Oh. The network helps show where Jae C. Oh may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200729
2 201223
3 201313
4 199413
5 200410
6 20179
7
Promoting Cooperation using "Kin" Biased Conditional Strategy in the Iterated Prisoner's Dilemma Game
20006
8
GameMosix: Game-Theoretic Middleware for CPU Sharing in Untrusted P2P Environment.
20046
9 20096
10 20116
11 20146
12
Effects of physical body on biased opponent selection in the Iterated Prisoner's Dilemma game
19995
13 20055
14 20055
15 20015
16 20164
17 19994
18 20044
19 20193
20 20183

About Jae C. Oh

Jae C. Oh is a scholar working on Computer Networks and Communications, Artificial Intelligence, Management Science and Operations Research, Information Systems and Sociology and Political Science, having authored 51 papers that have together received 211 indexed citations. Recurring topics across this work include Distributed and Parallel Computing Systems (9 papers), Evolutionary Algorithms and Applications (8 papers), Game Theory and Applications (6 papers), Distributed systems and fault tolerance (6 papers), Metaheuristic Optimization Algorithms Research (6 papers), Complex Network Analysis Techniques (6 papers), Modular Robots and Swarm Intelligence (5 papers) and Peer-to-Peer Network Technologies (5 papers). The work is most often cited by research in Hardware and Architecture (35 citations), Computer Networks and Communications (82 citations), Statistical and Nonlinear Physics (39 citations), Management Science and Operations Research (32 citations) and Computer Science Applications (10 citations). Jae C. Oh has collaborated with scholars based in United States, South Korea and Puerto Rico. Frequent co-authors include Daniel Mossé, Alexandre Ferreira, Alastair D. McAulay, K. Mehrotra, Jooyoung Lee, M. Haney, Lusha Wang, Wenliang Du, Jeffrey Saltz and Kishan G. Mehrotra. Their work appears in journals such as Applied Intelligence, Information Sciences, Knowledge and Information Systems, Artificial Intelligence Review and Experimental & Molecular Medicine.

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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