Eunmi Lee
- Immunology top 10%
-
- Advancements in Photolithography Techniques 4
-
- Streptococcal Infections and Treatments 3
- Neonatal and Maternal Infections 3
-
- Industrial Vision Systems and Defect Detection 3
-
- Tissue Engineering and Regenerative Medicine 2
-
- Liver physiology and pathology 2
-
- Muscle Physiology and Disorders 2
-
- Reproductive tract infections research 2
- Co-authors
- Do-Sik ShimRaziye PiranliogluJohn K. CowellDaniela MarascoMaria OuzounovaHasan KörkayaAhmed ChadliKhaled A. Hassan
- Cited by
- ImmunologyNeurologyOncology
- Partner nations
- South KoreaUnited StatesItaly
In The Last Decade
Eunmi Lee
36 papers receiving 745 citations
Peers
Comparison fields: 5 of 117
- Immunology 221
- Neurology 60
- Oncology 182
- Health Informatics 8
- Neurology 87
Countries citing papers authored by Eunmi Lee
This map shows the geographic impact of Eunmi 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 Eunmi Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eunmi Lee more than expected).
Fields of papers citing papers by Eunmi Lee
This network shows the impact of papers produced by Eunmi 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 Eunmi Lee. The network helps show where Eunmi Lee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Eunmi Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2023 | 16 | |
| 4 | 2023 | 3 | |
| 5 | 2023 | 2 | |
| 6 | 2022 | 1 | |
| 7 | 2022 | 8 | |
| 8 | 2020 | 31 | |
| 9 | 2019 | 93 | |
| 10 | 2018 | 30 | |
| 11 | 2018 | 9 | |
| 12 | 2017 | 287 | |
| 13 | 2016 | 0 | |
| 14 | 2016 | 1 | |
| 15 | An Implementation of Artificial Docent to Recommend Abstract Art | 2014 | 1 |
| 16 | A study on place storytelling using local folktales | 2012 | 0 |
| 17 | 2011 | 1 | |
| 18 | 2010 | 46 | |
| 19 | Test and performance comparison of end-to-end available bandwidth measurement tools | 2009 | 3 |
| 20 | The Estimation of Link Travel Time for Oversaturated Intersections from COSMOS Detector Data | 2007 | 1 |
About Eunmi Lee
Eunmi Lee is a scholar working on Microbiology, Industrial and Manufacturing Engineering and Computer Graphics and Computer-Aided Design, having authored 42 papers that have together received 759 indexed citations. Recurring topics across this work include Advancements in Photolithography Techniques (4 papers), Streptococcal Infections and Treatments (3 papers), Neonatal and Maternal Infections (3 papers), Industrial Vision Systems and Defect Detection (3 papers), Tissue Engineering and Regenerative Medicine (2 papers), Liver physiology and pathology (2 papers), Muscle Physiology and Disorders (2 papers) and Reproductive tract infections research (2 papers). The work is most often cited by research in Immunology (221 citations), Neurology (60 citations) and Oncology (182 citations). Eunmi Lee has collaborated with scholars based in South Korea, United States and Italy. Frequent co-authors include Do-Sik Shim, Raziye Piranlioglu, John K. Cowell, Daniela Marasco, Maria Ouzounova, Hasan Körkaya, Ahmed Chadli, Khaled A. Hassan, Ravindra Kolhe and Gang Zhou.
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.