Junghoon Chae

25 papers receiving 582 citations

Peers

Junghoon Chae
Comparison fields: 5 of 97
  • Transportation 100
  • Computer Vision and Pattern Recognition 253
  • Communication 85
  • Geography, Planning and Development 59
  • Statistical and Nonlinear Physics 125
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Russ Burtner United States
SungYe Kim United States
Sofiane Abbar Qatar
Shoko Wakamiya Japan
Sohaib Ghani United States
Abish Malik United States
Shehzad Afzal United States
Yukiko Kawai Japan
Carmela Comito Italy
Phong H. Nguyen United Kingdom
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Citations per year

Countries citing papers authored by Junghoon Chae

Since Specialization
Citations

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

Fields of papers citing papers by Junghoon Chae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012190
2 2013124
3 201162
4 201250
5 201648
6 201425
7 201721
8 202118
9 201616
10 201515
11 20207
12 20194
13 20214
14 20153
15 20153
16 20193
17 20202
18 20212
19 20212
20 20221

About Junghoon Chae

Junghoon Chae is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Statistical and Nonlinear Physics, Transportation and Sociology and Political Science, having authored 26 papers that have together received 605 indexed citations. Recurring topics across this work include Data Visualization and Analytics (14 papers), Complex Network Analysis Techniques (7 papers), Advanced Text Analysis Techniques (3 papers), Human Mobility and Location-Based Analysis (3 papers), Anomaly Detection Techniques and Applications (3 papers), Nutritional Studies and Diet (2 papers), Data Analysis with R (2 papers) and Public Relations and Crisis Communication (2 papers). The work is most often cited by research in Transportation (100 citations), Computer Vision and Pattern Recognition (253 citations), Communication (85 citations), Geography, Planning and Development (59 citations) and Statistical and Nonlinear Physics (125 citations). Junghoon Chae has collaborated with scholars based in United States, South Korea and Australia. Frequent co-authors include David S. Ebert, Yun Jang, Dennis Thom, Thomas Ertl, Ross Maciejewski, Harald Bosch, SungYe Kim, Carol J. Boushey, Edward J. Delp and Abish Malik. Their work appears in journals such as Computer Graphics Forum, Organizational Research Methods, Journal of Diabetes Science and Technology, Computers & Graphics and Transportation Research Part A Policy and Practice.

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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