Shinjae Yoo

5.9k total citations
140 papers, 1.9k citations indexed

About

Shinjae Yoo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Shinjae Yoo has authored 140 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Artificial Intelligence, 24 papers in Computer Vision and Pattern Recognition and 21 papers in Electrical and Electronic Engineering. Recurrent topics in Shinjae Yoo's work include Quantum Computing Algorithms and Architecture (13 papers), Solar Radiation and Photovoltaics (12 papers) and Anomaly Detection Techniques and Applications (12 papers). Shinjae Yoo is often cited by papers focused on Quantum Computing Algorithms and Architecture (13 papers), Solar Radiation and Photovoltaics (12 papers) and Anomaly Detection Techniques and Applications (12 papers). Shinjae Yoo collaborates with scholars based in United States, South Korea and China. Shinjae Yoo's co-authors include Samuel Yen-Chi Chen, Dantong Yu, Deyu Lu, Matthew R. Carbone, Hao Huang, Mehmet Topsakal, Dong Huang, Tzu-Chieh Wei, Yao-Lung L. Fang and John Heiser and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Nano Letters.

In The Last Decade

Shinjae Yoo

129 papers receiving 1.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shinjae Yoo United States 22 951 266 263 241 201 140 1.9k
Sheng Wang China 17 329 0.3× 185 0.7× 363 1.4× 207 0.9× 28 0.1× 158 1.6k
H. C. Watson Australia 25 1.3k 1.4× 215 0.8× 622 2.4× 210 0.9× 79 0.4× 93 4.0k
Jiwon Seo South Korea 29 306 0.3× 291 1.1× 729 2.8× 552 2.3× 77 0.4× 149 2.6k
Sandro Ridella Italy 24 1.3k 1.3× 613 2.3× 465 1.8× 115 0.5× 23 0.1× 136 3.1k
Ling Zhang China 17 360 0.4× 209 0.8× 225 0.9× 55 0.2× 93 0.5× 134 1.2k
Péter Révész United States 24 578 0.6× 145 0.5× 603 2.3× 446 1.9× 17 0.1× 159 2.5k
Lingli Wang China 27 265 0.3× 544 2.0× 1.1k 4.3× 465 1.9× 34 0.2× 259 2.8k
Guangwen Yang China 21 221 0.2× 121 0.5× 299 1.1× 303 1.3× 122 0.6× 141 1.8k
Bo Wang China 30 456 0.5× 137 0.5× 1.4k 5.5× 202 0.8× 51 0.3× 283 3.3k

Countries citing papers authored by Shinjae Yoo

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Wang, Jianhui, et al.. (2025). Quantum Reinforcement Learning for Volt-VAR Control in Power Distribution Systems. IEEE Open Access Journal of Power and Energy. 12. 833–844.
2.
Bryant, Alex K., Yuewei Lin, James M. Rae, et al.. (2024). Artificial intelligence to unlock real‐world evidence in clinical oncology: A primer on recent advances. Cancer Medicine. 13(12). e7253–e7253. 4 indexed citations
3.
Schipper, Matthew J., Lars G. Fritsche, Garth W. Strohbehn, et al.. (2024). Pan‐Cancer Survival Impact of Immune Checkpoint Inhibitors in a National Healthcare System. Cancer Medicine. 13(21). e70379–e70379. 4 indexed citations
4.
5.
Yoo, Shinjae, et al.. (2024). Utilizing a Hybrid Matrix Product State and Variational Quantum Circuit Architecture for the Detection of Kidney Diseases. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1821–1826.
6.
Wu, Kesheng, et al.. (2024). Understanding Data Access Patterns for dCache System. SHILAP Revista de lepidopterología. 295. 1053–1053. 1 indexed citations
7.
Deng, Yuefan, et al.. (2024). Exploring Robust Features for Improving Adversarial Robustness. IEEE Transactions on Cybernetics. 54(9). 5141–5151. 1 indexed citations
8.
Carbone, Matthew R., Hyeong Jin Kim, Shinjae Yoo, et al.. (2023). Flexible formulation of value for experiment interpretation and design. Matter. 7(2). 685–696. 4 indexed citations
9.
Kareem, Ahsan, et al.. (2023). Optimal sensor placement for reconstructing wind pressure field around buildings using compressed sensing. Journal of Building Engineering. 75. 106855–106855. 13 indexed citations
10.
Liang, Zhu, Mark S. Hybertsen, Xiaohui Qu, et al.. (2023). Uncertainty-aware predictions of molecular x-ray absorption spectra using neural network ensembles. Physical Review Research. 5(1). 19 indexed citations
11.
Park, David K., Seungsoo Kim, Yoonjung Yoonie Joo, et al.. (2023). Overestimated prediction using polygenic prediction derived from summary statistics. BMC Genomic Data. 24(1). 52–52. 1 indexed citations
12.
13.
Guo, Haoyue, Matthew R. Carbone, Chuntian Cao, et al.. (2023). Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes. Scientific Data. 10(1). 349–349. 19 indexed citations
14.
Park, Ji Hwan, Han Eol Cho, Jong Hun Kim, et al.. (2020). Machine learning prediction of incidence of Alzheimer’s disease using large-scale administrative health data. npj Digital Medicine. 3(1). 46–46. 83 indexed citations
15.
Liu, Ying, et al.. (2020). Electricity Load Forecasting with Collective Echo State Networks. 1–6. 3 indexed citations
16.
Lu, Deyu, Matthew R. Carbone, Mehmet Topsakal, & Shinjae Yoo. (2019). Using machine learning to predict local chemical environments from X-ray absorption spectra. Bulletin of the American Physical Society. 2019. 4 indexed citations
17.
18.
Huang, Hao, Shinjae Yoo, Dantong Yu, & Hong Qin. (2014). Noise-Resistant Unsupervised Feature Selection via Multi-perspective Correlations. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 210–219. 2 indexed citations
19.
Huang, Hao, Shinjae Yoo, Hong Qin, & Dantong Yu. (2011). A Robust Clustering Algorithm Based on Aggregated Heat Kernel Mapping. 270–279. 12 indexed citations
20.
Yoo, Shinjae, et al.. (2002). Comparison of CZCS and SeaWiFS Pigments for Merging the Higher Level Ocean Color Data. National Remote Sensing Bulletin. 18(5). 299–303. 1 indexed citations

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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