Shinjae Yoo
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Materials Chemistry
- Renewable Energy, Sustainability and the Environment top 10%
- Co-authors
- Samuel Yen-Chi ChenDantong YuDeyu LuMatthew R. CarboneHao HuangDong HuangMehmet TopsakalTzu-Chieh Wei
- Topics
- Quantum Computing Algorithms and Architecture (13 papers)Solar Radiation and Photovoltaics (12 papers)Anomaly Detection Techniques and Applications (12 papers)
- Journals
- Physical Review LettersSHILAP Revista de lepidopterologíaNano Letters
- Partner nations
- United StatesSouth KoreaChina
In The Last Decade
Shinjae Yoo
129 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 148
- Artificial Intelligence 951
- Computer Vision and Pattern Recognition 266
- Electrical and Electronic Engineering 263
- Materials Chemistry 241
- Renewable Energy, Sustainability and the Environment 201
Countries citing papers authored by Shinjae Yoo
This map shows the geographic impact of Shinjae Yoo'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 Shinjae Yoo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shinjae Yoo more than expected).
Fields of papers citing papers by Shinjae Yoo
This network shows the impact of papers produced by Shinjae Yoo. 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 Shinjae Yoo. The network helps show where Shinjae Yoo may publish in the future.
Co-authorship network of co-authors of Shinjae Yoo
This figure shows the co-authorship network connecting the top 25 collaborators of Shinjae Yoo. A scholar is included among the top collaborators of Shinjae Yoo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shinjae Yoo. Shinjae Yoo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 4 | |
| 6 | 1 | |
| 7 | 18 | |
| 8 | 1 | |
| 9 | 19 | |
| 10 | 1 | |
| 11 | 9 | |
| 12 | 19 | |
| 13 | 13 | |
| 14 | 11 | |
| 15 | 7 | |
| 16 | Detector Tomography on IBM Quantum Computers and Mitigation of Imperfect Measurement | 2 |
| 17 | Using machine learning to predict local chemical environments from X-ray absorption spectra | 4 |
| 18 | Re-examination of the Role of Latent Variables in Sequence Modeling | 1 |
| 19 | 1 | |
| 20 | Comparison of CZCS and SeaWiFS Pigments for Merging the Higher Level Ocean Color Data | 1 |
About Shinjae Yoo
Shinjae Yoo is a scholar working on Structural Biology, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 140 papers that have together received 1.9k indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (13 papers), Solar Radiation and Photovoltaics (12 papers) and Anomaly Detection Techniques and Applications (12 papers). The work is most often cited by research in Artificial Intelligence (951 citations), Structural Biology (30 citations) and Health Informatics (18 citations). Shinjae Yoo has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include Samuel Yen-Chi Chen, Dantong Yu, Deyu Lu, Matthew R. Carbone, Hao Huang, Dong Huang, Mehmet Topsakal, Tzu-Chieh Wei, Yao-Lung L. Fang and P.D. Kalb. Their work appears in journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Nano Letters.
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.