Ha‐Kyung Kong
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Sociology and Political Science
- Management Information Systems top 10%
- Human-Computer Interaction top 10%
- Co-authors
- Karrie KarahaliosZhicheng LiuJennifer G. KimHwajung HongWai‐Tat FuEric BlaisAditya ParameswaranBrian P. Bailey
- Topics
- Data Visualization and Analytics (6 papers)AI in Service Interactions (4 papers)Team Dynamics and Performance (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionHuman-Computer InteractionManagement Information Systems
- Journals
- Journal of the American Medical Informatics AssociationProceedings of the VLDB EndowmentComputer Graphics Forum
- Partner nations
- United StatesSouth KoreaCanada
In The Last Decade
Ha‐Kyung Kong
20 papers receiving 323 citations
Peers
Comparison fields: 5 of 72
- Computer Vision and Pattern Recognition 160
- Artificial Intelligence 95
- Sociology and Political Science 78
- Management Information Systems 46
- Human-Computer Interaction 37
Countries citing papers authored by Ha‐Kyung Kong
This map shows the geographic impact of Ha‐Kyung Kong'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 Ha‐Kyung Kong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ha‐Kyung Kong more than expected).
Fields of papers citing papers by Ha‐Kyung Kong
This network shows the impact of papers produced by Ha‐Kyung Kong. 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 Ha‐Kyung Kong. The network helps show where Ha‐Kyung Kong may publish in the future.
Co-authorship network of co-authors of Ha‐Kyung Kong
This figure shows the co-authorship network connecting the top 25 collaborators of Ha‐Kyung Kong. A scholar is included among the top collaborators of Ha‐Kyung Kong 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 Ha‐Kyung Kong. Ha‐Kyung Kong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 13 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 10 | |
| 8 | 14 | |
| 9 | 9 | |
| 10 | 9 | |
| 11 | 23 | |
| 12 | 56 | |
| 13 | 71 | |
| 14 | 24 | |
| 15 | 40 | |
| 16 | 4 | |
| 17 | Parental Perceptions, Experiences, and Desires of Music Therapy. | 3 |
| 18 | 5 | |
| 19 | 46 | |
| 20 | Plexlines: Tracking Socio-communicative Behaviors Using Timeline Visualizations. | 4 |
About Ha‐Kyung Kong
Ha‐Kyung Kong is a scholar working on Applied Psychology, Human-Computer Interaction and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 343 indexed citations. Recurring topics across this work include Data Visualization and Analytics (6 papers), AI in Service Interactions (4 papers) and Team Dynamics and Performance (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (160 citations), Human-Computer Interaction (37 citations) and Management Information Systems (46 citations). Ha‐Kyung Kong has collaborated with scholars based in United States, South Korea and Canada. Frequent co-authors include Karrie Karahalios, Zhicheng Liu, Jennifer G. Kim, Hwajung Hong, Wai‐Tat Fu, Eric Blais, Aditya Parameswaran, Brian P. Bailey, Wenjie Zhu and Sajjadur Rahman. Their work appears in journals such as Journal of the American Medical Informatics Association, Proceedings of the VLDB Endowment and Computer Graphics Forum.
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.