Jon-Lark Kim

1.5k citations
80 papers · 899 indexed · h-index 16

Impact in

Papers in

Jon-Lark Kim

74 papers receiving 848 citations

Peers

Jon-Lark Kim
Comparison fields: 5 of 36
  • Discrete Mathematics and Combinatorics 252
  • Artificial Intelligence 859
  • Computer Networks and Communications 327
  • Computational Theory and Mathematics 223
  • Electrical and Electronic Engineering 542
Replace Victor Zinoviev with:
Victor Zinoviev Russia
Harold N. Ward United States
Yanfeng Qi China
S.M. Dodunekov Bulgaria
Xiang‐dong Hou United States
H. F. Mattson United States
Iwan Duursma United States
Simeon Ball Spain
Chengju Li China
Longjiang Qu China
Jon-Lark Kim relative to Victor Zinoviev Russia Victor Zinoviev's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jon-Lark Kim

Since Specialization
Citations

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

Fields of papers citing papers by Jon-Lark Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jon-Lark Kim. 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 Jon-Lark Kim. The network helps show where Jon-Lark Kim may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20242
4 20230
5 20234
6 20232
7 20234
8 20216
9 20189
10 20172
11 20133
12
Type i Codes over GF(4)
20121
13 20126
14
Selected Unsolved Problems in Coding Theory (Applied and Numerical Harmonic Analysis)
20111
15 20114
16 200712
17 200615
18 200512
19 200374
20
On Additive GF(4) Codes
200115

About Jon-Lark Kim

Jon-Lark Kim is a scholar working on Discrete Mathematics and Combinatorics, Artificial Intelligence, Computer Networks and Communications, Computational Theory and Mathematics and Electrical and Electronic Engineering, having authored 80 papers that have together received 899 indexed citations. Recurring topics across this work include Coding theory and cryptography (72 papers), graph theory and CDMA systems (45 papers), Finite Group Theory Research (22 papers), Cooperative Communication and Network Coding (20 papers), Error Correcting Code Techniques (16 papers), Cellular Automata and Applications (8 papers), DNA and Biological Computing (6 papers) and Quantum Computing Algorithms and Architecture (6 papers). The work is most often cited by research in Discrete Mathematics and Combinatorics (252 citations), Artificial Intelligence (859 citations), Computer Networks and Communications (327 citations), Computational Theory and Mathematics (223 citations) and Electrical and Electronic Engineering (542 citations). Jon-Lark Kim has collaborated with scholars based in South Korea, United States and France. Frequent co-authors include Yoonjin Lee, Steven T. Dougherty, Patrick Solé, Hongwei Liu, T. Aaron Gulliver, Lin Sok, Buket Özkaya, W. Cary Huffman, Minjia Shi and Vera Pless. Their work appears in journals such as Designs Codes and Cryptography, IEEE Transactions on Information Theory, Finite Fields and Their Applications, Discrete Mathematics and Advances in Mathematics of Communications.

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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