publication
conferences / journals / preprints / workshops
underline: advised student
*: co-first authors
*: co-first authors
2024
WoLF: Large Language Model Framework for CXR UnderstandingÂ
Seil Kang, Donghyun Kim, Junhyeok Kim, Hyo Kyung Lee, Seong Jae Hwang
arXiv, 2024.
[arxiv]
CoBra: Complementary Branch Fusing Class and Semantic Knowledge for Robust Weakly Supervised Semantic SegmentationÂ
Woojung Han, Seil Kang, Kyobin Choo, Seong Jae Hwang
arXiv, 2024.
[arxiv]
Advancing Text-Driven Chest X-Ray Generation with Policy-Based Reinforcement LearningÂ
Woojung Han*, Chanyoung Kim*, Dayun Ju, Yumin Shim, Seong Jae Hwang
arXiv, 2024.
[arxiv]
EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation
Chanyoung Kim*, Woojung Han*, Dayun Ju, Seong Jae Hwang
Computer Vision and Pattern Recognition (CVPR), 2024. [Highlight (11% of accepted papers, 2.8% of submitted papers)]
[Project Page] [arxiv]
2023
MISPEL: A supervised deep learning method for harmonizing multi-scanner neuroimaging data
Mahbaneh Eshghzadeh Torbati, Davneet S. Minhas, Charles M. Laymon, Pauline Maillard, James D. Wilson, Chang-Le Chen, Ciprian M. Crainiceanu, Charles S. DeCarli, Seong Jae Hwang, Dana L. Tudorascu
Medical Image Analysis (MIA), 2023. [Impact Factor: 13.828]
[MIA]
Domain Adversarial Neural Networks for Domain Generalization: When It Works and How to Improve
Anthony Sicilia, Xingchen Zhao, Seong Jae Hwang
Machine Learning, 2023. [Impact Factor: 7.5]
Evidence-empowered Transfer Learning for Alzheimer's Disease
Kai Ong, Hana Kim, Minjin Kim, Jinseong Jang, Beomseok Sohn, Yoon Seong Choi, Dosik Hwang, Seong Jae Hwang and Jinyoung Yeo
IEEE International Symposium on Biomedical Imaging (ISBI), 2023.
[arxiv]
2022
PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners
Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang
Conference on Uncertainty in Artificial Intelligence (UAI), 2022. [Best Paper Award (1 of 712 submitted papers)]
Test-time Fourier Style Calibration for Domain Generalization
Xingchen Zhao, Chang Liu, Anthony Sicilia, Seong Jae Hwang, Yun Fu
International Joint Conference on Artificial Intelligence (IJCAI), 2022.
The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error
Katherine Atwell, Anthony Sicilia, Seong Jae Hwang, Malihe Alikhani
Findings of ACL, 2022.
Anatomic development of the upper airway during the first five years of life: A three-dimensional imaging study
Ying Ji Chuang, Seong Jae Hwang, Kevin A Buhr, Courtney A Miller, Gregory D Avey, Brad H Story, Houri K. Vorperian
PLOS ONE, 2022.
2021
A multi-scanner neuroimaging data harmonization using RAVEL and ComBat
Mahbaneh Eshghzadeh Torbati, Davneet S. Minhas, Ghasan Ahmad, Erin E. O'Connor, John Muschelli, Charles Laymon, Zixi Yang, Annie Cohen, Howard J. Aizenstein, William E. Klunk, Bradley T. Christian, Seong Jae Hwang, Ciprian M. Crainiceanu, Dana L. Tudorascu
NeuroImage, 2021.
Multi-scanner Harmonization of Paired Neuroimaging Data via Structure Preserving Embedding Learning
Mahbaneh Eshghzadeh Torbati, Dana L. Tudorascu, Pauline Maillard, Davneet S. Minhas, Charles S. DeCarli, Seong Jae Hwang
The First Workshop on Computer Vision for Automated Medical Diagnosis (CVAMD), International Conference on Computer Vision (W-ICCV), 2021. [Oral]
Point Cloud Augmentation with Weighted Local Transformations
Sihyeon Kim, Sanghyeok Lee, Dasol Hwang, Jaewon Lee, Seong Jae Hwang, Hyunwoo Kim
International Conference on Computer Vision (ICCV), 2021.
PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging
Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh, Seong Jae Hwang
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.
Cycle Consistent Embedding of 3D Brains with Auto-Encoding Generative Adversarial Networks
Shibo Xing, Harsh Sinha, Seong Jae Hwang
Medical Imaging with Deep Learning (Short Paper - MIDL), 2021.
Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders
Xin Ma, Guorong Wu, Seong Jae Hwang, Won Hwa Kim
Information Processing in Medical Imaging (IPMI), 2021. [Acceptance rate: 30.0%]
Multi-Domain Learning by Meta-Learning: Taking Optimal Steps in Multi-Domain Loss Landscapes by Inner-Loop Learning
Anthony Sicilia, Xingchen Zhao, Davneet Minhas, Erin O'Connor, Howard Aizenstein, William Klunk, Dana Tudorascu, Seong Jae Hwang
IEEE International Symposium on Biomedical Imaging (ISBI), 2021.
Robust White Matter Hyperintensity Segmentation on Unseen Domain
Xingchen Zhao, Anthony Sicilia, Davneet Minhas, Erin O'Connor, Howard Aizenstein, William Klunk, Dana Tudorascu, Seong Jae Hwang
IEEE International Symposium on Biomedical Imaging (ISBI), 2021.
2020
Developmental morphology of the cervical vertebrae and the emergence of sexual dimorphism in size and shape: A computed tomography study
Courtney A. Miller, Seong Jae Hwang, Meghan M. Cotter, Houri K. Vorperian
The Anatomical Record, 2020.
Classifying Nuclei Shape Heterogeneity in Breast Tumors with Skeletons
Brian Faulkenstein, Adriana Kovashka, Seong Jae Hwang, S. Chakra Chennubhotla
Workshop on BioImage Computing, European Conference on Computer Vision (ECCV Workshop), 2020. [Oral Presentation]
[Springer link] [openreview pdf]
Learning Amyloid Pathology Progression from Longitudinal PiB-PET Images in Preclinical Alzheimer's Disease
Wei Hao, Nicholas M. Vogt, Zihang Meng, Seong Jae Hwang, Rebecca L. Koscik, Sterling C. Johnson, Barbara B. Bendlin, Vikas Singh
IEEE International Symposium on Biomedical Imaging (ISBI), 2020.
2019
Statistical Analysis of Longitudinally and Conditionally Generated Neuroimaging Measures via Conditional Recurrent Flow
Seong Jae Hwang, Zirui Tao, Won Hwa Kim, Vikas Singh
The First Workshop on Statistical Deep Learning in Computer Vision, International Conference on Computer Vision (W-ICCV), 2019. [Oral]
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging
Seong Jae Hwang, Zirui Tao, Won Hwa Kim, Vikas Singh
International Conference on Computer Vision (ICCV), 2019. [Acceptance rate: 25%]
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging
Seong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh
Conference on Uncertainty in Artificial Intelligence (UAI), 2019. [Acceptance rate: 26%]
Large-Scale Training Framework for Video Annotation
Seong Jae Hwang, Joonseok Lee, Balakrishnan Varadarajan, Ariel Gordon, Zheng Xu, Paul Natsev
Conference on Knowledge Discovery and Data Mining (KDD), 2019. [Oral acceptance rate: 9.2%] [Oral]
Cervical vertebral growth and emergence of sexual dimorphism: A developmental study using computed tomography
Courtney A. Miller, Seong Jae Hwang, Meghan M. Cotter, Houri K. Vorperian
Journal of Anatomy, 2019.
2018
Cerebrospinal fluid biomarkers of neurofibrillary tangles and synaptic dysfunction are associated with longitudinal decline in white matter connectivity: A multi-resolution graph analysis
Won Hwa Kim, Annie M. Racine, Nagesh Adluru, Seong Jae Hwang, Kaj Blennow, Henrik Zetterberg, Cyhthia M. Carlsson, Sanjay Asthana, Rebecca L. Koscik, Sterling C. Johnson, Barbara B.Bendlin, Vikas Singh
NeuroImage: Clinical, 2018.
Associations between PET Amyloid Pathology and DTI Brain Connectivity in Preclinical Alzheimer's Disease
Seong Jae Hwang, Nagesh Adluru, Won Hwa Kim, Sterling C. Johnson, Barbara B. Bendlin, Vikas Singh
Brain Connectivity, 2018.
Tensorize, Factorize and Regularize: Robust Visual Relationship Learning
Seong Jae Hwang, Sathya N. Ravi, Zirui Tao, Hyunwoo J. Kim, Maxwell D. Collins, Vikas Singh
Computer Vision and Pattern Recognition (CVPR), 2018. [Acceptance rate: 29.7%]
2017
Online Graph Completion: Multivariate Signal Recovery in Computer Vision
Won Hwa Kim, Mona Jalal, Seong Jae Hwang, Sterling C. Johnson, Vikas Singh
Computer Vision and Pattern Recognition (CVPR), 2017.
2016
Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging
Won Hwa Kim, Seong Jae Hwang, Nagesh Adluru, Sterling C. Johnson, Vikas Singh
European Conference on Computer Vision (ECCV), 2016. [Acceptance rate: 26.6%]
Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks
Seong Jae Hwang, Nagesh Adluru, Maxwell D. Collins, Sathya N. Ravi, Barbara B. Bendlin, Sterling C. Johnson, Vikas Singh
Computer Vision and Pattern Recognition (CVPR), 2016. [Acceptance rate: 29.9%]
[pdf] [supplementary] [poster] [code will be available here] [project page]
2015
A Projection free method for Generalized Eigenvalue Problem with a nonsmooth Regularizer
Seong Jae Hwang, Maxwell D. Collins, Sathya N. Ravi, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson, Vikas Singh
International Conference on Computer Vision (ICCV), 2015. [Acceptance rate: 30.9%]
[pdf] [fixed eq (18),(20)] [supplementary] [poster] [code] [project page] [PubMed]
conference abstracts
2022
Reducing MRI Inter-Scanner Variability Using 3D Superpixel ComBat
Chang-Le Chen, Mahbaneh Eshaghzadeh Torbati, James D. Wilson, Davneet S. Minhas, Charles M. Laymon, Seong Jae Hwang, Pauline Maillard, Evan Fletcher, Charles S. DeCarli, Dana L. Tudorascu
Alzheimer's Association International Conference (AAIC), 2022.
2021
An MRI multi-scanner neuroimaging data harmonization study using RAVEL and ComBat
Mahbaneh Eshghzadeh Torbati, Davneet S. Minhas, Ghasan Ahmad, Erin E. O'Connor, John Muschelli, Charles Laymon, Zixi Yang, Annie Cohen, Howard J. Aizenstein, William E. Klunk, Bradley T. Christian, Ciprian M. Crainiceanu, Seong Jae Hwang, Dana L. Tudorascu
Alzheimer's Association International Conference (AAIC), 2021.
2020
Retrospective prediction of amyloid accumulation trajectories in a risk-enriched Alzheimer's disease cohort with sequential neural networks
Seong Jae Hwang, Rebecca L. Koscik, Tobey J. Betthauser, Zirui Tao, Won Hwa Kim, Sterling C. Johnson, Vikas Singh
Human Amyloid Imaging (HAI), 2020. [poster]
2019
Predicting amyloid accumulation trajectories in a risk-enriched Alzheimer's disease cohort with Deep Conditional Neural Networks
Seong Jae Hwang, Rebecca L. Koscik, Tobey J. Betthauser, Zirui Tao, Won Hwa Kim, Sterling C. Johnson, Vikas Singh
Alzheimer's Association International Conference (AAIC), 2019.
A Normative Modeling Based Analysis of Amyloid, Cognition, and Tau in Preclinical Alzheimer's Disease
Zirui Tao, Ronak R. Mehta, Seong Jae Hwang, Rebecca L. Koscik, Erin Jonaitis, Sterling C. Johnson, Vikas Singh
Alzheimer's Association International Conference (AAIC), 2019.
Sequential Deep Learning Algorithms show structural connectivity differences by amyloid status
Xingjian Zhen, Rudrasis Chakraborty, Nocholas Vogt, Seong Jae Hwang, Sterling C. Johnson, Barbara B. Bendlin, Vikas Singh
Alzheimer's Association International Conference (AAIC), 2019.
2018
Data-Driven Propagation Modeling of PET-Derived Alzheimer's Pathology in a Preclinical Cohort
Seong Jae Hwang, Sathya N. Ravi, Nagesh Adluru, Barbara B. Bendlin, Sterling C. Johnson, Vikas Singh
Alzheimer's Association International Conference (AAIC), 2018.
2017
Graph Completion: A Generalization of Netflix Prize Problem to Designing Cost Effective Neuroimaging Trials in Preclinical AD
Won Hwa Kim, Seong Jae Hwang, Nagesh Adluru, Sterling C. Johnson, Vikas Singh
Alzheimer's Association International Conference (AAIC), 2017.
2016
Multi-Resolution Analysis of DTI-Derived Brain Connectivity and the Influence of PET-Derived Alzheimer's Disease Pathology in a Preclinical Cohort
Seong Jae Hwang, Won Hwa Kim, Barbara B. Bendlin, Nagesh Adluru, Vikas Singh
Alzheimer's Association International Conference (AAIC), 2016. [Oral]
patents
Framework for Training Machine-Learned Models on Extremely Large Datasets
Joon Seok Lee, Balakrishnan Varadarajan, Ariel Gordon, Apostol Ivanov Natsev, Seong Jae Hwang
US Patent, 2021, US20210117728A1
Neural Network Architecture with Concurrent Uncertainty Output
Seong Jae Hwang, Ronak Mehta, Vikas Singh
US Patent, 2020, US20200065648A1
Computerized System for Efficient Augmentation of Data Sets
Won Hwa Kim, Seong Jae Hwang, Nagesh Adluru, Sterling Johnson, Vikas Singh
US Patent, 2018, US20180113990A1
Fast object tracking framework for sports video recognition
Zheng Han, Xiaowei Dai, Seong Jae Hwang, Jason Fass
US Patent, 2016, US9449230B2