Sungwon Jung
- Signal Processing top 5%
- Computer Networks and Communications top 5%
- Molecular Biology
- Artificial Intelligence
- Information Systems top 10%
- Co-authors
- Sakti PramanikJianping HuaChao SimaHyuk‐Chul KwonByungkyu LeeYang ZhongJohn H. BeamanDoheon Lee
- Topics
- Data Management and Algorithms (12 papers)Caching and Content Delivery (7 papers)Advanced Database Systems and Queries (7 papers)
- Partner nations
- South KoreaUnited StatesIndia
In The Last Decade
Sungwon Jung
41 papers receiving 401 citations
Peers
Comparison fields: 5 of 71
- Signal Processing 174
- Computer Networks and Communications 167
- Molecular Biology 83
- Artificial Intelligence 75
- Information Systems 60
Countries citing papers authored by Sungwon Jung
This map shows the geographic impact of Sungwon Jung'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 Sungwon Jung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sungwon Jung more than expected).
Fields of papers citing papers by Sungwon Jung
This network shows the impact of papers produced by Sungwon Jung. 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 Sungwon Jung. The network helps show where Sungwon Jung may publish in the future.
Co-authorship network of co-authors of Sungwon Jung
This figure shows the co-authorship network connecting the top 25 collaborators of Sungwon Jung. A scholar is included among the top collaborators of Sungwon Jung based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sungwon Jung. Sungwon Jung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 1 | |
| 7 | Clustering Non-Ordered Discrete Data * | 4 |
| 8 | 3 | |
| 9 | 69 | |
| 10 | 6 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 6 | |
| 14 | Enabling Large-Scale Bayesian Network Learning by Preserving Intercluster Directionality(Artificial Intelligence and Cognitive Science) | 1 |
| 15 | 5 | |
| 16 | 4 | |
| 17 | 22 | |
| 18 | An Efficient Learning Method for Large Bayesian Networks using Clustering | 3 |
| 19 | 28 | |
| 20 | 6 |
About Sungwon Jung
Sungwon Jung is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence, having authored 46 papers that have together received 434 indexed citations. Recurring topics across this work include Data Management and Algorithms (12 papers), Caching and Content Delivery (7 papers) and Advanced Database Systems and Queries (7 papers). The work is most often cited by research in Signal Processing (174 citations), Computer Networks and Communications (167 citations) and Geography, Planning and Development (36 citations). Sungwon Jung has collaborated with scholars based in South Korea, United States and India. Frequent co-authors include Sakti Pramanik, Jianping Hua, Chao Sima, Hyuk‐Chul Kwon, Byungkyu Lee, Yang Zhong, John H. Beaman, Doheon Lee, Sunggeun Park and Tae‐Won Park. Their work appears in journals such as IEEE Access, Sensors and IEEE Transactions on Knowledge and Data Engineering.
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.