Sukjun Lee

14 papers receiving 237 citations

Peers

Sukjun Lee
Comparison fields: 5 of 87
  • Organic Chemistry 73
  • Biophysics 13
  • Computer Vision and Pattern Recognition 43
  • Public Health, Environmental and Occupational Health 56
  • Pharmacology 15
Replace Chakresh Kumar Jain with:
Chakresh Kumar Jain India
Gurubasavaraj V. Pujar India
Daniel O’Shea Ireland
Uma Roy India
Mohamed A. Kassem Egypt
Ling Liang China
Yanhui Zhang China
Ewelina Węglarz‐Tomczak Poland
Jeffrey M. Schaub United States
P. N. Marshall United Kingdom
Sukjun Lee relative to Chakresh Kumar Jain India Chakresh Kumar Jain's profile →
Citations per field
00.5×4.7×
Chakresh Kumar Jain · 1×
Citations per year

Countries citing papers authored by Sukjun Lee

Since Specialization
Citations

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

Fields of papers citing papers by Sukjun Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 201340
2 201735
3 201429
4 201621
5 201420
6 202119
7 201418
8 201317
9 202314
10 201413
11 20237
12 20223
13 20212
14 20152
15
Acne Severity Scoring Using Deep Learning
20181
16 20220
17 20160

About Sukjun Lee

Sukjun Lee is a scholar working on Public Health, Environmental and Occupational Health, Molecular Biology, Materials Chemistry, Information Systems and Oncology, having authored 17 papers that have together received 241 indexed citations. Recurring topics across this work include Malaria Research and Control (6 papers), Mosquito-borne diseases and control (4 papers), Metal-Organic Frameworks: Synthesis and Applications (2 papers), Traditional and Medicinal Uses of Annonaceae (1 paper), Acne and Rosacea Treatments and Effects (1 paper), Pharmacological Effects and Toxicity Studies (1 paper), MicroRNA in disease regulation (1 paper) and Bone health and osteoporosis research (1 paper). The work is most often cited by research in Organic Chemistry (73 citations), Biophysics (13 citations), Computer Vision and Pattern Recognition (43 citations), Public Health, Environmental and Occupational Health (56 citations) and Pharmacology (15 citations). Sukjun Lee has collaborated with scholars based in South Korea, United States and Cameroon. Frequent co-authors include Lawrence Ayong, Lúcio H. Freitas-Júnior, Eun‐Young Lee, Yu Yuan, Debopam Chakrabarti, Guo N. Huang, Myungjoo Kang, Michael A. E. Hansen, Seung‐Hyun Moon and Michel Liuzzi. Their work appears in journals such as International Journal for Parasitology Drugs and Drug Resistance, CrystEngComm, Applied Surface Science, ChemSusChem and Molecular Cell.

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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