Seong Jae Hwang

590 total citations
33 papers, 303 citations indexed

About

Seong Jae Hwang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Seong Jae Hwang has authored 33 papers receiving a total of 303 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 14 papers in Artificial Intelligence and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Seong Jae Hwang's work include Advanced Neuroimaging Techniques and Applications (9 papers), Functional Brain Connectivity Studies (8 papers) and Domain Adaptation and Few-Shot Learning (8 papers). Seong Jae Hwang is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (9 papers), Functional Brain Connectivity Studies (8 papers) and Domain Adaptation and Few-Shot Learning (8 papers). Seong Jae Hwang collaborates with scholars based in United States, South Korea and Sweden. Seong Jae Hwang's co-authors include Hyunwoo J. Kim, Vikas Singh, Maxwell D. Collins, Davneet Minhas, Dana Tudorascu, Nagesh Adluru, Sanghyeok Lee, Jaewon Lee, Sterling C. Johnson and Barbara B. Bendlin and has published in prestigious journals such as PLoS ONE, NeuroImage and Scientific Reports.

In The Last Decade

Seong Jae Hwang

26 papers receiving 294 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seong Jae Hwang United States 10 98 86 73 39 25 33 303
Suat Toraman Türkiye 12 71 0.7× 198 2.3× 227 3.1× 74 1.9× 15 0.6× 33 601
Tian Siva Tian United States 6 46 0.5× 93 1.1× 137 1.9× 187 4.8× 17 0.7× 10 520
Mikhail Belyaev Russia 6 88 0.9× 146 1.7× 88 1.2× 55 1.4× 5 0.2× 18 360
Annegreet van Opbroek Netherlands 7 138 1.4× 157 1.8× 114 1.6× 14 0.4× 6 0.2× 11 355
A. Shahina India 11 55 0.6× 118 1.4× 47 0.6× 80 2.1× 14 0.6× 41 327
Andrea U. J. Mewes United States 8 417 4.3× 150 1.7× 278 3.8× 50 1.3× 21 0.8× 8 878
Beanbonyka Rim South Korea 9 37 0.4× 59 0.7× 141 1.9× 79 2.0× 13 0.5× 11 362
Joseph S. Shin South Korea 9 134 1.4× 9 0.1× 49 0.7× 43 1.1× 8 0.3× 17 276

Countries citing papers authored by Seong Jae Hwang

Since Specialization
Citations

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

Fields of papers citing papers by Seong Jae Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seong Jae Hwang. 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 Seong Jae Hwang. The network helps show where Seong Jae Hwang may publish in the future.

Co-authorship network of co-authors of Seong Jae Hwang

This figure shows the co-authorship network connecting the top 25 collaborators of Seong Jae Hwang. A scholar is included among the top collaborators of Seong Jae Hwang 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 Seong Jae Hwang. Seong Jae Hwang 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.
Lee, Sangwon, et al.. (2025). Deep Learning–Based Precontrast CT Parcellation for MRI-Free Brain Amyloid PET Quantification. Clinical Nuclear Medicine. 50(5). e262–e270.
2.
3.
Hong, Jau‐Shyong, et al.. (2025). A prediction model of pediatric bone density from plain spine radiographs using deep learning. Scientific Reports. 15(1). 13039–13039.
4.
5.
Hwang, Seong Jae, et al.. (2024). Complementary branch fusing class and semantic knowledge for robust weakly supervised semantic segmentation. Pattern Recognition. 157. 110922–110922. 3 indexed citations
6.
Chen, Chang‐Le, Davneet Minhas, Charles M. Laymon, et al.. (2024). Superpixel-ComBat modeling: A joint approach for harmonization and characterization of inter-scanner variability in T1-weighted images. Imaging Neuroscience. 2.
7.
Hwang, Seong Jae, et al.. (2023). Domain adversarial neural networks for domain generalization: when it works and how to improve. Machine Learning. 112(7). 2685–2721. 46 indexed citations
8.
Minhas, Davneet, Charles M. Laymon, Pauline Maillard, et al.. (2023). MISPEL: A supervised deep learning harmonization method for multi-scanner neuroimaging data. Medical Image Analysis. 89. 102926–102926. 9 indexed citations
9.
Kim, Hana, Jinseong Jang, Beomseok Sohn, et al.. (2023). Evidence-Empowered Transfer Learning for Alzheimer’s Disease. 1–5. 3 indexed citations
10.
Liu, Chang, et al.. (2022). Test-time Fourier Style Calibration for Domain Generalization. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 1721–1727. 14 indexed citations
11.
Hwang, Seong Jae, et al.. (2021). Cycle Consistent Embedding of 3D Brains with Auto-Encoding Generative Adversarial Networks. 2 indexed citations
12.
Tudorascu, Dana, et al.. (2021). Multi-scanner Harmonization of Paired Neuroimaging Data via Structure Preserving Embedding Learning. PubMed. 2021. 3277–3286. 13 indexed citations
13.
Minhas, Davneet, Erin E. O’Connor, Howard Aizenstein, et al.. (2021). Robust White Matter Hyperintensity Segmentation On Unseen Domain. PubMed. 2021. 1047–1051. 8 indexed citations
14.
Lee, Sanghyeok, et al.. (2021). Point Cloud Augmentation with Weighted Local Transformations. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 528–537. 33 indexed citations
15.
Lee, Dong Yeon, et al.. (2020). A modified transfibular technique of ankle arthrodesis using partial fibular resection and onlay bone graft. PLoS ONE. 15(10). e0241141–e0241141. 13 indexed citations
16.
Hwang, Seong Jae, Joonseok Lee, Balakrishnan Varadarajan, et al.. (2019). Large-Scale Training Framework for Video Annotation. 2394–2402. 1 indexed citations
17.
Hwang, Seong Jae, Nagesh Adluru, Won Hwa Kim, et al.. (2018). Associations Between Positron Emission Tomography Amyloid Pathology and Diffusion Tensor Imaging Brain Connectivity in Pre-Clinical Alzheimer's Disease. Brain Connectivity. 9(2). 162–173. 9 indexed citations
18.
Kim, Won Hwa, Annie M. Racine, Nagesh Adluru, et al.. (2018). Cerebrospinal fluid biomarkers of neurofibrillary tangles and synaptic dysfunction are associated with longitudinal decline in white matter connectivity: A multi-resolution graph analysis. NeuroImage Clinical. 21. 101586–101586. 21 indexed citations
19.
Kim, Won Hwa, Seong Jae Hwang, Nagesh Adluru, Sterling C. Johnson, & Vikas Singh. (2016). Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging. Lecture notes in computer science. 9910. 188–205. 2 indexed citations
20.
Hwang, Seong Jae, Maxwell D. Collins, Vamsi Krishna Ithapu, et al.. (2015). A Projection Free Method for Generalized Eigenvalue Problem with a Nonsmooth Regularizer. PubMed. 27. 1841–1849. 6 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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