Sungahn Ko

963 citations
36 papers · 546 · h-index 13

Impact in

Papers in

Sungahn Ko

34 papers receiving 525 citations

Peers

Sungahn Ko
Comparison fields: 5 of 109
  • Computer Vision and Pattern Recognition 223
  • Transportation 63
  • Signal Processing 71
  • Human-Computer Interaction 33
  • Building and Construction 74
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Sungahn Ko relative to Christian Jacob Canada Christian Jacob's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sungahn Ko

Since Specialization
Citations

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

Fields of papers citing papers by Sungahn Ko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Osteocalcin promoter-based toxic gene therapy for the treatment of osteosarcoma in experimental models.
199675
2 201969
3 201648
4 200040
5 202040
6 201131
7 201228
8
STGRAT: A Spatio-Temporal Graph Attention Network for Traffic Forecasting.
201927
9 202223
10 201223
11 201616
12 202214
13 201413
14 202212
15 201312
16 200111
17 202110
18 20218
19 20168
20 20127

About Sungahn Ko

Sungahn Ko is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Sociology and Political Science, Signal Processing and Building and Construction, having authored 36 papers that have together received 546 indexed citations. Recurring topics across this work include Data Visualization and Analytics (20 papers), Traffic Prediction and Management Techniques (5 papers), Virus-based gene therapy research (3 papers), Complex Network Analysis Techniques (3 papers), Video Analysis and Summarization (3 papers), Anomaly Detection Techniques and Applications (3 papers), Data Analysis with R (3 papers) and Cell Image Analysis Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (223 citations), Transportation (63 citations), Signal Processing (71 citations), Human-Computer Interaction (33 citations) and Building and Construction (74 citations). Sungahn Ko has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include David S. Ebert, Ross Maciejewski, Seungmin Jin, Niklas Elmqvist, Yun Jang, Chinghai Kao, Robert A. Sikes, Gérard Karsenty, Toshiro Shirakawa and Bum Chul Kwon. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, IEEE Transactions on Biomedical Engineering, International Journal of Radiation Oncology*Biology*Physics and Media and 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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