Jae Chung

658 citations
30 papers · 359 · h-index 9

Impact in

Papers in

Jae Chung

25 papers receiving 339 citations

Peers

Jae Chung
Comparison fields: 5 of 63
  • Computer Networks and Communications 140
  • Computer Vision and Pattern Recognition 91
  • Cardiology and Cardiovascular Medicine 80
  • Radiology, Nuclear Medicine and Imaging 81
  • Health Information Management 17
Replace Murtaza Ali Khan with:
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Citations per field
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Citations per year

Countries citing papers authored by Jae Chung

Since Specialization
Citations

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

Fields of papers citing papers by Jae Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011174
2 201825
3 200322
4 201821
5
MEASUREMENT OF THE CONGESTION RESPONSIVENESS OF REALPLAYER STREAMING VIDEO OVER UDP
200314
6 202112
7 200012
8
BETTER-BEHAVED, BETTER-PERFORMING MULTIMEDIA NETWORKING
200011
9 20038
10 20188
11 20117
12
Dynamic-CBT - Better Performing Active Queue Management for Multimedia Networking
20007
13
FairPlayer or FoulPlayer? - Head to Head Performance of RealPlayer Streaming Video Over UDP versus TCP
20026
14 20065
15 20185
16
MTP: A Streaming-Friendly Transport Protocol
20054
17
Congestion control for streaming media
20054
18 20223
19 20223
20 20232

About Jae Chung

Jae Chung is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence and Cardiology and Cardiovascular Medicine, having authored 30 papers that have together received 359 indexed citations. Recurring topics across this work include Network Traffic and Congestion Control (20 papers), Software-Defined Networks and 5G (10 papers), Caching and Content Delivery (7 papers), Advanced Wireless Network Optimization (6 papers), Image and Video Quality Assessment (5 papers), Peer-to-Peer Network Technologies (5 papers), Advanced Optical Network Technologies (3 papers) and Wireless Networks and Protocols (3 papers). The work is most often cited by research in Computer Networks and Communications (140 citations), Computer Vision and Pattern Recognition (91 citations), Cardiology and Cardiovascular Medicine (80 citations), Radiology, Nuclear Medicine and Imaging (81 citations) and Health Information Management (17 citations). Jae Chung has collaborated with scholars based in United States, New Zealand and Germany. Frequent co-authors include Mark Claypool, Brett R. Cowan, João A.C. Lima, Kalyanam Shivkumar, Alan H. Kadish, Daniel Lee, Pau Medrano−Gracia, Peter Hunter, David A. Bluemke and Alistair A. Young. Their work appears in journals such as Bioinformatics, Journal of Cardiovascular Magnetic Resonance, Multimedia Tools and Applications, IEEE Access and International Journal of Engineering & Technology.

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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