Jun Jo
Impact in
- Architecture top 1%
- Building and Construction top 2%
- Building Energy and Comfort Optimization
Papers in
-
- Context-Aware Activity Recognition Systems 7
- Video Surveillance and Tracking Methods 7
-
- Advanced Graph Neural Networks 9
- Co-authors
- John S. Gero (2 shared papers)Hong Guan (4 shared papers)Yong Oh Lee (3 shared papers)Jeonghye Han (2 shared papers)Miheon Jo (1 shared paper)Jay S. Golden (3 shared papers)Thành Tâm Nguyên (19 shared papers)D.‐Y. Kim (1 shared paper)
- Journals
- IEEE Access (3 papers)Australasian Marketing Journal (AMJ) (2 papers)International Journal of Consumer Studies (2 papers)Information Sciences (2 papers)IEEE Transactions on Knowledge and Data Engineering (2 papers)
- Partner nations
- AustraliaSouth KoreaVietnam
In The Last Decade
Jun Jo
135 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 168
- Architecture 51
- Building and Construction 284
- Geology 110
- Polymers and Plastics 265
- Computer Science Applications 103
Countries citing papers authored by Jun Jo
This map shows the geographic impact of Jun Jo'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 Jun Jo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Jo more than expected).
Fields of papers citing papers by Jun Jo
This network shows the impact of papers produced by Jun Jo. 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 Jun Jo. The network helps show where Jun Jo may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Jo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 162 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Ubiquitous learning environment: An adaptive teaching system using ubiquitous technology | 2004 | 222 |
| 2 | 2007 | 184 | |
| 3 | 2008 | 176 | |
| 4 | 1998 | 132 | |
| 5 | 2017 | 126 | |
| 6 | 2018 | 120 | |
| 7 | 2020 | 119 | |
| 8 | 2017 | 117 | |
| 9 | 2022 | 115 | |
| 10 | 2015 | 105 | |
| 11 | 2009 | 86 | |
| 12 | 2007 | 62 | |
| 13 | 2011 | 60 | |
| 14 | 2018 | 57 | |
| 15 | Future Schools and How Technology can be used to support Millennial and Generation-Z Students | 2007 | 55 |
| 16 | 2019 | 52 | |
| 17 | 2016 | 44 | |
| 18 | 2009 | 42 | |
| 19 | 2019 | 41 | |
| 20 | 2022 | 39 |
About Jun Jo
Jun Jo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Biomedical Engineering and Information Systems, having authored 162 papers that have together received 2.9k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (9 papers), Non-Invasive Vital Sign Monitoring (8 papers), Infrastructure Maintenance and Monitoring (8 papers), Color perception and design (7 papers), Context-Aware Activity Recognition Systems (7 papers), Consumer Perception and Purchasing Behavior (7 papers), Video Surveillance and Tracking Methods (7 papers) and Remote Sensing and LiDAR Applications (6 papers). The work is most often cited by research in Architecture (51 citations), Building and Construction (284 citations), Geology (110 citations), Polymers and Plastics (265 citations) and Computer Science Applications (103 citations). Jun Jo has collaborated with scholars based in Australia, South Korea and Vietnam. Frequent co-authors include John S. Gero, Hong Guan, Yong Oh Lee, Jeonghye Han, Miheon Jo, Jay S. Golden, Thành Tâm Nguyên, D.‐Y. Kim, Sang‐Soon Kim and Giyoong Tae. Their work appears in journals such as IEEE Access, Australasian Marketing Journal (AMJ), International Journal of Consumer Studies, Information Sciences 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.