Hakjun Hyun
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Viral Infections and Vectors
Papers in
-
- SARS-CoV-2 and COVID-19 Research 15
- COVID-19 Clinical Research Studies 12
- SARS-CoV-2 detection and testing 3
- Epidemiology 15
- Influenza Virus Research Studies 6
- Pneumonia and Respiratory Infections 5
- Hepatitis B Virus Studies 3
- Co-authors
- Hee Jin Cheong (34 shared papers)Woo Joo Kim (35 shared papers)Joon Young Song (35 shared papers)Ji Yun Noh (31 shared papers)Hye Seong (27 shared papers)Jin Gu Yoon (31 shared papers)Yu Bin Seo (12 shared papers)Min Joo Choi (11 shared papers)
- Journals
- Journal of Korean Medical Science (8 papers)Vaccine (3 papers)Frontiers in Immunology (3 papers)The Journal of Infectious Diseases (3 papers)Medicine (2 papers)
- Partner nations
- South KoreaJapanUnited States
In The Last Decade
Hakjun Hyun
36 papers receiving 371 citations
Peers
Comparison fields: 5 of 83
- Modeling and Simulation 69
- Infectious Diseases 208
- Health 59
- Neurology 48
- Epidemiology 84
Countries citing papers authored by Hakjun Hyun
This map shows the geographic impact of Hakjun Hyun'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 Hakjun Hyun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hakjun Hyun more than expected).
Fields of papers citing papers by Hakjun Hyun
This network shows the impact of papers produced by Hakjun Hyun. 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 Hakjun Hyun. The network helps show where Hakjun Hyun may publish in the future.
Co-authors
The 25 scholars most cited alongside Hakjun Hyun, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 124 | |
| 2 | 2016 | 27 | |
| 3 | 2021 | 24 | |
| 4 | 2020 | 22 | |
| 5 | 2016 | 20 | |
| 6 | 2021 | 16 | |
| 7 | 2021 | 14 | |
| 8 | 2016 | 13 | |
| 9 | 2022 | 11 | |
| 10 | 2021 | 11 | |
| 11 | 2022 | 8 | |
| 12 | 2023 | 8 | |
| 13 | 2022 | 8 | |
| 14 | 2023 | 6 | |
| 15 | 2023 | 5 | |
| 16 | 2023 | 5 | |
| 17 | 2022 | 5 | |
| 18 | 2023 | 4 | |
| 19 | 2022 | 4 | |
| 20 | 2024 | 4 |
About Hakjun Hyun
Hakjun Hyun is a scholar working on Infectious Diseases, Epidemiology, Health, Modeling and Simulation and Microbiology, having authored 38 papers that have together received 379 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (15 papers), COVID-19 Clinical Research Studies (12 papers), Vaccine Coverage and Hesitancy (8 papers), Influenza Virus Research Studies (6 papers), Pneumonia and Respiratory Infections (5 papers), COVID-19 epidemiological studies (4 papers), Hepatitis B Virus Studies (3 papers) and SARS-CoV-2 detection and testing (3 papers). The work is most often cited by research in Modeling and Simulation (69 citations), Infectious Diseases (208 citations), Health (59 citations), Neurology (48 citations) and Epidemiology (84 citations). Hakjun Hyun has collaborated with scholars based in South Korea, Japan and United States. Frequent co-authors include Hee Jin Cheong, Woo Joo Kim, Joon Young Song, Ji Yun Noh, Hye Seong, Jin Gu Yoon, Yu Bin Seo, Min Joo Choi, Won Suk Choi and Jacob Lee. Their work appears in journals such as Journal of Korean Medical Science, Vaccine, Frontiers in Immunology, The Journal of Infectious Diseases and Medicine.
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.