Daejun Park

21 papers receiving 854 citations

Peers

Daejun Park
Comparison fields: 5 of 29
  • Information Systems 381
  • Software 65
  • Artificial Intelligence 424
  • Computational Theory and Mathematics 76
  • Computer Networks and Communications 94
Replace Mithun P. Acharya with:
Mithun P. Acharya United States
Ivica Nikolić Singapore
Ralf Sasse Switzerland
Allen P. Nikora United States
Alexander Grebhahn Germany
Thomas T. Pressburger United States
Pierre Genevès France
Kirk Webb United States
Sebastian Bănescu Germany
Ihor Kuz Australia
Daejun Park relative to Mithun P. Acharya United States Mithun P. Acharya's profile →
Citations per field
00.5×5×11.9×
Mithun P. Acharya · 1×
Citations per year

Countries citing papers authored by Daejun Park

Since Specialization
Citations

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

Fields of papers citing papers by Daejun Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Daejun Park, 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 Daejun Park Line = papers co-authored together Daejun Park links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018319
2 201997
3 201887
4 201586
5 201776
6 201657
7 201944
8
iJournaling: Fine-Grained Journaling for Improving the Latency of Fsync System Call
201726
9 201420
10 201619
11 201512
12 20189
13 20188
14 20203
15 20142
16 20152
17 20131
18 20151
19
Adaptive Edge-Directed Interpolation Using Edge Map Analysis
20171
20
Modified New Edge-Directed Interpolation Using Window Extension
20171

About Daejun Park

Daejun Park is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Signal Processing and Computational Theory and Mathematics, having authored 22 papers that have together received 873 indexed citations. Recurring topics across this work include Logic, programming, and type systems (11 papers), Advanced Image Processing Techniques (5 papers), Advanced Data Storage Technologies (3 papers), Formal Methods in Verification (2 papers), Video Coding and Compression Technologies (2 papers), UAV Applications and Optimization (1 paper), Cryptography and Data Security (1 paper) and Network Security and Intrusion Detection (1 paper). The work is most often cited by research in Information Systems (381 citations), Software (65 citations), Artificial Intelligence (424 citations), Computational Theory and Mathematics (76 citations) and Computer Networks and Communications (94 citations). Daejun Park has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Grigore Roşu, Andrei R Stefanescu, Manasvi Saxena, Philip Daian, Brandon M. Moore, Nishant Rodrigues, Xiaoran Zhu, Seungwan Hong, Jung Hee Cheon and Kyoohyung Han. Their work appears in journals such as IEEE Access, ACM SIGPLAN Notices, ACM Transactions on Programming Languages and Systems, Journal of Automated Reasoning and International journal of communication.

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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