Geon Kim

1.3k total citations
25 papers, 795 citations indexed

About

Geon Kim is a scholar working on Atomic and Molecular Physics, and Optics, Biophysics and Biomedical Engineering. According to data from OpenAlex, Geon Kim has authored 25 papers receiving a total of 795 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Atomic and Molecular Physics, and Optics, 9 papers in Biophysics and 7 papers in Biomedical Engineering. Recurrent topics in Geon Kim's work include Digital Holography and Microscopy (21 papers), Cell Image Analysis Techniques (7 papers) and Advanced X-ray Imaging Techniques (5 papers). Geon Kim is often cited by papers focused on Digital Holography and Microscopy (21 papers), Cell Image Analysis Techniques (7 papers) and Advanced X-ray Imaging Techniques (5 papers). Geon Kim collaborates with scholars based in South Korea, United States and United Kingdom. Geon Kim's co-authors include YongKeun Park, Hyun‐Seok Min, YoungJu Jo, Hyungjoo Cho, Seungwoo Shin, Sang‐Yun Lee, Moosung Lee, Kyoohyun Kim, KyeoReh Lee and DongHun Ryu and has published in prestigious journals such as Nature Communications, Blood and Nature Cell Biology.

In The Last Decade

Geon Kim

24 papers receiving 763 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Geon Kim South Korea 14 496 320 279 177 149 25 795
Krishnarao Tangella United States 16 544 1.1× 283 0.9× 427 1.5× 251 1.4× 79 0.5× 37 952
Moosung Lee South Korea 14 400 0.8× 220 0.7× 261 0.9× 131 0.7× 97 0.7× 29 633
Alborz Feizi United States 12 586 1.2× 271 0.8× 343 1.2× 226 1.3× 303 2.0× 22 1.0k
Toyohiko Yamauchi Japan 14 448 0.9× 204 0.6× 484 1.7× 162 0.9× 110 0.7× 34 870
Hassaan Majeed United States 13 312 0.6× 184 0.6× 175 0.6× 137 0.8× 59 0.4× 20 550
Seungwoo Shin South Korea 15 799 1.6× 300 0.9× 461 1.7× 229 1.3× 168 1.1× 27 1.1k
Daniel Boss Switzerland 12 831 1.7× 435 1.4× 439 1.6× 231 1.3× 261 1.8× 23 1.0k
Matthew T. Rinehart United States 12 519 1.0× 222 0.7× 403 1.4× 311 1.8× 179 1.2× 21 865
Itay Barnea Israel 15 349 0.7× 199 0.6× 260 0.9× 142 0.8× 129 0.9× 40 951
Shan Shan Kou China 17 635 1.3× 118 0.4× 382 1.4× 218 1.2× 97 0.7× 41 911

Countries citing papers authored by Geon Kim

Since Specialization
Citations

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

Fields of papers citing papers by Geon Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Geon Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Geon Kim. A scholar is included among the top collaborators of Geon Kim 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 Geon Kim. Geon Kim 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.
Shin, Su‐Jin, Geon Kim, Hyungjoo Cho, et al.. (2025). Revealing 3D microanatomical structures of unlabeled thick cancer tissues using holotomography and virtual H&E staining. Nature Communications. 16(1). 4781–4781. 5 indexed citations
2.
Kim, Geon, Hervé Hugonnet, Kyoohyun Kim, et al.. (2024). Holotomography. Nature Reviews Methods Primers. 4(1). 24 indexed citations
3.
Kim, Geon, Meaghan Boileau, Thuy T. P. Nguyen, et al.. (2024). In Vivo barcoded CRISPR-Cas9 Screen Identifies Ncoa4-mediated Ferritinophagy As a Dependence in Tet2-Deficient Haemopoiesis. Blood. 144(Supplement 1). 188–188.
4.
Park, Ju Yeon, Bijie Bai, DongHun Ryu, et al.. (2023). Artificial intelligence-enabled quantitative phase imaging methods for life sciences. Nature Methods. 20(11). 1645–1660. 68 indexed citations
5.
6.
Lee, Dohyeon, et al.. (2023). Enhanced functionalities of immune cells separated by a microfluidic lattice: assessment based on holotomography. Biomedical Optics Express. 14(12). 6127–6127. 1 indexed citations
7.
Kim, Geon, DongHun Ryu, Hervé Hugonnet, et al.. (2023). Label‐free histological analysis of retrieved thrombi in acute ischemic stroke using optical diffraction tomography and deep learning. Journal of Biophotonics. 16(8). e202300067–e202300067. 5 indexed citations
8.
Kim, Geon, Minhee Kang, DongHun Ryu, et al.. (2022). Rapid species identification of pathogenic bacteria from a minute quantity exploiting three-dimensional quantitative phase imaging and artificial neural network. Light Science & Applications. 11(1). 190–190. 43 indexed citations
9.
Jo, YoungJu, Hyungjoo Cho, Wei Sun Park, et al.. (2021). Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning. Nature Cell Biology. 23(12). 1329–1337. 78 indexed citations
10.
Chung, Hyungjin, et al.. (2021). Missing Cone Artifact Removal in ODT Using Unsupervised Deep Learning in the Projection Domain. IEEE Transactions on Computational Imaging. 7. 747–758. 21 indexed citations
11.
Chung, Hyungjin, et al.. (2021). Unsupervised Missing Cone Deep Learning in Optical Diffraction Tomography.. 1 indexed citations
12.
Ryu, DongHun, YoungJu Jo, Young Seo Kim, et al.. (2019). Deep learning-based optical field screening for robust optical diffraction tomography. Scientific Reports. 9(1). 15239–15239. 19 indexed citations
13.
14.
Chung, Taek, Sung‐Im Do, Kiyong Na, et al.. (2018). Stromal p16 Overexpression in Gastric-type Mucinous Carcinoma of the Uterine Cervix. Anticancer Research. 38(6). 3551–3558. 19 indexed citations
15.
Jung, JaeHwang, Seong-Joo Hong, Geon Kim, et al.. (2018). Label-free non-invasive quantitative measurement of lipid contents in individual microalgal cells using refractive index tomography. Scientific Reports. 8(1). 6524–6524. 65 indexed citations
16.
Kim, Geon, SangYun Lee, Seungwoo Shin, & YongKeun Park. (2018). Three-dimensional label-free imaging and analysis of Pinus pollen grains using optical diffraction tomography. Scientific Reports. 8(1). 1782–1782. 24 indexed citations
17.
Kim, Geon, YoungJu Jo, Hyungjoo Cho, Hyun‐Seok Min, & YongKeun Park. (2018). Learning-based screening of hematologic disorders using quantitative phase imaging of individual red blood cells. Biosensors and Bioelectronics. 123. 69–76. 52 indexed citations
18.
Kim, Geon, YoungJu Jo, Hyungjoo Cho, et al.. (2018). Automated Identification of Bacteria using Three-Dimensional Holographic Imaging and Convolutional Neural Network. 1–2. 7 indexed citations
19.
Jo, YoungJu, Hyungjoo Cho, Sang‐Yun Lee, et al.. (2018). Quantitative Phase Imaging and Artificial Intelligence: A Review. IEEE Journal of Selected Topics in Quantum Electronics. 25(1). 1–14. 141 indexed citations
20.
Lee, KyeoReh, Kyoohyun Kim, Geon Kim, Seungwoo Shin, & YongKeun Park. (2017). Time-multiplexed structured illumination using a DMD for optical diffraction tomography. Optics Letters. 42(5). 999–999. 100 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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