Publications

Roza G. Bayrak, Colin B. Hansen, Jorge A. Salas, Nafis Ahmed, Ilwoo Lyu, Mara Mather, Yuankai Huo, Catie Chang, "DeepPhysioRecon: Tracing peripheral physiology in low frequency fMRI dynamics", Imaging Neuroscience, 2025.

Joonhyuk Park*, Donghyun Lee*, Yujee Song, Guorong Wu, Won Hwa Kim, "Topology-aware Graph Diffusion Model with Persistent Homology", Neural Information Processing Systems (NeurIPS), 2025. [*: equal contribution]

Seungeun Lee, Seunghwan Lee, Sunghwa Ryu, Ilwoo Lyu, "SPHARM-Reg: Unsupervised Cortical Surface Registration using Spherical Harmonics", IEEE Transactions on Medical Imaging (TMI), 2025.

Seungeun Lee, Seunghwan Lee, Ethan Willbrand, Benjamin Parker, Silvia Bunge, Kevin Weiner, Ilwoo Lyu, "Leveraging Input-Level Feature Deformation with Guided-Attention for Sulcal Labeling", IEEE Transactions on Medical Imaging (TMI), 2025.

Seungeun Lee, Sergey Pyatkovskiy, Jaejun Yoo, Ilwoo Lyu, “Spherical Diffusion Process for Score‑Guided Cortical Correspondence via Spectral Attention”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025.

Seunghun Baek, Jaejin Lee, Jaeyoon Sim, Minjae Jeong, Won Hwa Kim, “MNM: Multi-level Neuroimaging Meta-analysis with Hyperbolic Brain-Text Representations”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025. [Provisional accept: ~9%] 

Hyuna Cho, Hayoung Ahn, Guorong Wu, Won Hwa Kim, “Adaptive Adversarial Data Augmentation with Trajectory Constraint for Alzheimer’s Disease Conversion Prediction”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025. [Provisional accept: ~9%]

Joonhyuk Park, Donghyun Lee, Guorong Wu, Won Hwa Kim, “Conditional Graph Diffusion with Topological Constraints for Brain Network Generation”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025.

Wooseok Jung*, Joonhyuk Park*, Won Hwa Kim, “DISCLOSE the Neurodegeneration Dynamics: Individualized ODE Discovery for Alzheimer’s Disease Precision Medicine”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025. [Oral presentation, *: equal contribution]

Sungyoon Jung, Donghyun Lee, Won Hwa Kim, “MindLink: Subject-agnostic Cross-Subject Brain Decoding Framework”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025.

Hyuna Cho, Ziquan Wei, Seungjoo Lee, Tingting Dan, Guorong Wu, Won Hwa Kim, “Conditional Diffusion Model using Ordinal Regression for Longitudinal Neurodegenerative Data Generation”, Alzheimer’s Association International Conference (AAIC), 2025. 

Sehyung Cheong, Hoseok Lee, Won Hwa Kim, “Survey on Sampling Conditioned Brain Images and Imaging Measures with Generative Models”, Biomedical Engineering Letters (BMEL), 2025. 

Inho Kim, Youngkil Song, Jicheol Park, Won Hwa Kim, Suha Kwak, "Improving Sound Source Localization with Joint Slot Attention on Image and Audio", Computer Vision and Pattern Recognition (CVPR), Nashville, 2025.

Yongsik Sim, Changmin Seo, Young-gun Lee, Byoung Seok Ye, Ilwoo Lyu, Beomseok Sohn, "Local Gyrification Index and Sulcal Depth as Imaging Markers of Cognitive Decline in Alzheimer's Disease", Frontiers in Aging Neuroscience, 2025.

Hyuna Cho, Ziquan Wei, Seungjoo Lee, Tingting Dan, Guorong Wu, Won Hwa Kim, “Conditional Diffusion with Ordinal Regression: Longitudinal Data Generation for Neurodegenerative Disease Studies”, International Conference on Learning Representations (ICLR), 2025. [Spotlight: ~5.1%] 

Minjae Jeong*, Yechan Hwang*, Jaejin Lee, Sungyoon Jung, Won Hwa Kim, “HGM³: Hierarchical Generative Masked Motion Modeling with Hard Token Mining”, International Conference on Learning Representations (ICLR), 2025. [*: equal contribution] 

Hyeonwoo Cho, Chanmin Park, Dong-hee Kim, Jinyoung Kim, Won Hwa Kim, "CNG-SFDA: Clean-and-Noisy Region Guided Online-Offline Source-Free Domain Adaptation", Asian Conference on Computer Vision (ACCV), 2024.

Wooseok Jung, Saehyun Kim, Dong-hee Kim, Won Hwa Kim, "Modelling Brain Atrophy Dynamics Enhances Predicting Cognitive Decline in Alzheimer’s Disease Continuum", Cognitive Computational Neuroscience (CCN), 2024.

Minjae Jeong*, Hyuna Cho*, Sungyoon Jung, Won Hwa Kim, "Uncertainty-aware Diffusion-based Adversarial Attack for Realistic Colonoscopy Image Synthesis", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024. [Provisional Accept: ~11%, *: equal contribution]

Seunghun Baek*, Jaeyoon Sim*, Guorong Wu, Won Hwa Kim, "OCL: Ordinal Contrastive Learning for Imputating Features with Progressive Labels", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024. [Provisional Accept: ~11%, *: equal contribution] 

Yanquan Huang, Tingting Dan, Won Hwa Kim, Guorong Wu, “Uncovering Cortical Pathways of Prion-like Pathology Spreading in Alzheimer’s Disease by Neural Optimal Mass Transport”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024. [Provisional accept: ~11%] 

Yechan Hwang, Soojin Hwang, Guorong Wu, Won Hwa Kim, “Multi-order Simplex-based Graph Neural Network for Brain Network Analysis”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024. 

Jaeyoon Sim, Minjae Lee, Guorong Wu, Won Hwa Kim, “Multi-Modal Graph Neural Network with Transformer-Guided Adaptive Diffusion for Preclinical Alzheimer Classification”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024. 

Tingting Dan, Mustafa Dere, Won Hwa Kim, Minjeong Kim, Guorong Wu, "TauFlowNet: Revealing latent propagation mechanism of tau aggregates using deep neural transport equations", Medical Image Analysis (MedIA), 2024. 

Hyuna Cho, Jaeyoon Sim, Guorong Wu, Won Hwa Kim, "Neurodegenerative Brain Network Classification via Adaptive Diffusion with Temporal Regularization", International Conference on Machine Learning (ICML), 2024. 

Tingting Dan, Ziquan Wei, Won Hwa Kim, Guorong Wu, "Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold", International Conference on Machine Learning (ICML), 2024. 

Seunghun Baek*, Jaeyoon Sim*, Mustafa Dere, Minjeong Kim, Guorong Wu, Won Hwa Kim, "Modality-Agnostic Style Transfer for Holistic Feature Imputation",  International Symposium on Biomedical Imaging (ISBI), 2024. [Oral presentation, *: equal contribution] 

Yujee Song, Donghyun Lee, Rui Meng, Won Hwa Kim, "Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations",  International Conference on Learning Representations (ICLR), 2024. 

Inhyuk Park, Won Hwa Kim, Jongbin Ryu, "Style-KD: Class-imbalanced medical image classification via style knowledge distillation", Biomedical Signal Processing and Control, 2024. [Impact factor: 5.1] 

Jaeyoon Sim, Sooyeon Jeon, Injun Choi, Guorong Wu, Won Hwa Kim, "Learning to Approximate Adaptive Kernel Convolution on Graphs", AAAI Conference on Artificial Intelligence (AAAI), 2024. 

Hyuna Cho, Yubin Han, Amal Isaiah, Won Hwa Kim, "Covariate Correcting Network for Isolating the Impact of Long-term SES Changes on Brain Development", Annual Meeting of the Organization for Human Brain Mapping (OHBM), 2024 

Joonhyuk Park*, Yechan Hwang*, Minjeong Kim, Moo K. Chung, Guorong Wu, Won Hwa Kim, "Brain Connectome Analysis for Alzheimer’s Disease using Hodge Laplacian-based Edge Convolution", Annual Meeting of the Organization for Human Brain Mapping (OHBM), 2024. [*: equal contribution] 

Hyuna Cho, Injun Choi, Suha Kwak, Won Hwa Kim, "Interactive Network Perturbation between Teacher and Students for Semi-Supervised Semantic Segmentation", Winter Conference on Applications of Computer Vision (WACV), 2024. [Accepted in the first round: 92/815 = ~11%] 

Hyuna Cho, Minjae Jeong, Sooyeon Jeon, Sungsoo Ahn, Won Hwa Kim, "Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion",  Neural Information Processing Systems (NeurIPS), 2023.

Tingting Dan, Jiaqi Ding, Ziquan Wei, Shahar Z Kovalsky, Minjeong Kim, Won Hwa Kim, Guorong Wu, "Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals", Neural Information Processing Systems (NeurIPS), 2023.

Tingting Dan, Minjeong Kim, Won Hwa Kim, Guorong Wu, "Developing Explainable Deep Model for Discovering Novel Control Mechanism of Neuro-Dynamics", IEEE Transactions on Medical Imaging (TMI), 2023.

Hyuna Cho, Guorong Wu, Won Hwa Kim, "Mixing Temporal Graphs with MLP for Longitudinal Brain Connectome Analysis", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023. [Oral Presentation: 68/2250 = ~3%] 

Hyuna Cho, Yubin Han, Won Hwa Kim, "Anti-Adversarial Consistency Regularization for Data Augmentation: Applications to Robust Medical Image Segmentation", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023. [Provisional Accept: ~14%] 

Joonhyuk Park*, Yechan Hwang*, Minjeong Kim, Moo K. Chung, Guorong Wu, Won Hwa Kim, "Convolving Directed Graph Edges via Hodge Laplacian for Brain Network Analysis", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023. [Provisional Accept: ~14%] [*: equal contribution] 

Ellen Jieun Oh, Yechan Hwang, Yubin Han, Taegeun Choi, Geunyoung Lee, Won Hwa Kim, "RESToring Clarity: Unpaired Retina Image Enhancement using Scattering Transform", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023.  

Tingting Dan, Minjeong Kim, Won Hwa Kim, Guorong Wu, "Enhance Early Diagnosis Accuracy of Alzheimer's Disease by Elucidating Interactions between Amyloid Cascade and Tau Propagation", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023.

Tingting Dan, Minjeong Kim, Won Hwa Kim, Guorong Wu, "TauFlowNet: Uncovering Propagation Mechanism of Tau Aggregates by Neural Transport Equation", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023. 

Tingting Dan, Minjeong Kim, Won Hwa Kim, Guorong Wu, "Uncovering Structural-Functional Coupling Alterations for Neurodegenerative Diseases", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023. 

Jinhyeok Jang, Woo-han Yun, Won Hwa Kim, Youngwoo Yoon, Jaehong Kim, Jaeyeon Lee, ByungOk Han, "Learning to Boost Training by Periodic Nowcasting Near Future Weights", International Conference on Machine Learning (ICML), 2023. 

Rui Meng, Fan Yang, Won Hwa Kim, "Dynamic Covariance Estimation via Predictive Wishart Process with an Application on Brain Connectivity Estimation", Computational Statistics & Data Analysis (CSDA), 2023. 

Hyuna Cho, Guorong Wu, Won Hwa Kim, "Spatio-Temporal Multi-Layer Perceptron for Longitudinal Brain Connectome Analysis", Annual Meeting of the Organization for Human Brain Mapping (OHBM) , 2023. 

Deunsol Jung, Sanghyun Kim, Won Hwa Kim, Minsu Cho, "Devil's on the Edges: Selective Quad Attention for Scene Graph Generation", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. 

Huan Liu*, Tingting Dan*, Zhuobin Huang, Defu Yang, Won Hwa Kim,  Minjeong Kim, Paul Laurienti, Guorong Wu, "HoloBrain: A Harmonic Holography for Self-organized Brain Function",  Information Processing in Medical Imaging (IPMI), 2023.  [*: equal contribution] 

Seunghun Baek, Injun Choi, Mustafa Dere, Minjeong Kim, Guorong Wu, Won Hwa Kim, "Learning Covariance-based Multi-scale Representation of NeuroImaging Measures for Alzheimer Classification",  IEEE International Symposium on Biomedical Imaging (ISBI), 2023. 

Kurt Schilling, Derek Archer, Francois Rheault, Ilwoo Lyu, Yuankai Huo, Leon Cai, Silvia Bunge, Kevin Weiner, John Gore, Adam Anderson, Bennett Landman, "Superficial white matter across the lifespan: volume, thickness, change, and relationship with cortical features", Brain Structure and Function, 2023.

Zachary Stoebner, Kilian Hett, Ilwoo Lyu, Hans Johnson, Jane Paulsen, Jeffrey Long, Ipek Oguz, "Comprehensive shape analysis of the cortex in Huntington’s disease", Human Brain Mapping, 2023.

Yue Liu, Shunxing Bao, Dario Englot, Victoria Morgan, Warren Taylor, Ying Wei, Ipek Oguz, Bennett Landman, Ilwoo Lyu, "Hierarchical particle optimization for cortical shape correspondence in temporal lobe resection", Computers in Biology and Medicine, 2023.

Injun Choi, Guorong Wu, Won Hwa Kim, "How Much to Aggregate: Learning Adaptive Node-wise Scales on Graphs for Brain Networks", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022. [Acceptance rate: 31%] 

Tingting Dan, Hongmin Cai, Zhuobin Huang, Paul Laurenti, Won Hwa Kim, Guorong Wu, "Neuro-RDM: An Explainable Neural Network Landscape of Reaction-Diffusion Model for Cognitive Task Recognition", Medical Image Computing and Computer Assisted Intervention  (MICCAI), 2022. [Acceptance rate: 31%]  

Gangin Park, Chunsan Hong, Bohyung Kim, Won Hwa Kim, "What Do Untargeted Adversarial Examples Reveal in Medical Image Segmentation?", Uncertainty for Safe Utilization of Machine Learning in Medical Imaging  (UNSURE), 2022. 

Xin Ma, Won Hwa Kim, "Locally Normalized Soft Contrastive Clustering for Compact Clusters",   International Joint Conference on Artificial Intelligence (IJCAI), 2022. [Acceptance rate: 15%] 

Hyuna Cho*, Feng Tong, Sungyong You, Sungyoung Jung, Won Hwa Kim, Jayoung Kim, "Prediction of the Immune Phenotypes of Bladder Cancer Patients for Precision Oncology", IEEE Open Journal of Engineering in Medicine and Biology, 2022 [*: Hyuna advised by WHKim] 

Hyuna Cho, Gunwoong Park, Amal Isaiah, Won Hwa Kim, "Covariate Correcting Network for Detecting Sole Effect of Socioeconomic Status on Brain in Children",  Annual Meeting of the Organization for Human Brain Mapping (OHBM), 2022. 

Fan Yang, Guorong Wu, Won Hwa Kim, "Disentangled Representation of Longitudinal β-Amyloid for AD via Sequential Graph Variational Autoencoder with Supervision", IEEE International Symposium on Biomedical Imaging (ISBI), 2022.   

Shunxing Bao, Brian Boyd, Praitayini Kanakaraj, Karthik Ramadass, Francisco Meyer, Yuqian Liu, William Duett, Yuankai Huo, Ilwoo Lyu, David Zald, Seth Smith, Baxter Rogers, Bennett Landman, "Integrating the BIDS neuroimaging data format and workflow optimization for large-scale medical image analysis", Journal of Digital Imaging, 2022.

Abel Worku Tessema, Hansol Lee, Yelim Gong, HwaPyeong Cho, Hamdia Murad Adem, Ilwoo Lyu, Jae-Hyeok Lee, HyungJoon Cho, "Automated volumetric determination of high R₂* regions in substantia nigra: a feasibility study of quantifying substantia nigra atrophy in progressive supranuclear palsy", NMR in Biomedicine, 2022.

Seungbo Ha, Ilwoo Lyu, "SPHARM-Net: Spherical Harmonics-based Convolution for Cortical Parcellation", IEEE Transactions on Medical Imaging (TMI), 2022.

Ethan Willbrand, Benjamin Parker, Willa Voorhies, Jacob Miller, Ilwoo Lyu, Tyler Hallock, Lyndsey Aponik-Gremillion, Seth Koslov, Alzheimer’s Disease Neuroimaging Initiative, Silvia Bunge, Brett Foster, Kevin Weiner, "Uncovering a tripartite landmark in posterior cingulate cortex", Science Advances, 2022.

Maxwell Roeske, Ilwoo Lyu, Maureen McHugo, Jeniffer Blackford, Neil Woodward, Stephan Heckers, "Incomplete hippocampal inversion: a neurodevelopmental mechanism for hippocampal shape deformation in schizophrenia", Biological Psychiatry, 2022.

Yue Liu, Yuankai Huo, Blake Dewey, Ying Wei, Ilwoo Lyu, Bennett Landman, "Generalizing Deep Learning Brain Segmentation for Skull Removal and Intra-Cranial Measurements", Magnetic Resonance Imaging, 2022.

Roza Bayrak, Ilwoo Lyu, Catie Chang, “Learning Subject‑Specific Functional Parcellations from Cortical Surface Measures”, MICCAI Workshop on Predictive Intelligence in Medicine (PRIME), 2022.

Hyuna Cho, Gunwoong Park, Amal Isaiah, Won Hwa Kim, "Covariate Correcting Networks for Identifying Associations between Socioeconomic Factors and Brain Outcomes in Children", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.   

Fan Yang*, Rui Meng*, Hyuna Cho, Guorong Wu, Won Hwa Kim, "Disentangled Sequential Graph Autoencoder for Preclinical Alzheimer's Disease Characterizations from ADNI study", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.  [*: Equal contribution] 

Xin Ma, Guorong Wu,  Seongjae Hwang, Won Hwa Kim, "Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders", International Conference on Information Processing in Medical Imaging (IPMI), 2021. 

Debapriya Banerjee, Maria Kyrarini, Won Hwa Kim, "Image-Label Recovery on Fashion Data Using Image Similarity from Triple Siamese Network '',  Technologies, 2021. 

Alisa Zoltowski, Ilwoo Lyu, Michelle Failla, Lisa Mash, Kacie Dunham, Jacob Feldman, Tiffany Woynaroski, Mark Wallace, Laura Barquero, Tin Nguyen, Laurie Cutting, Hakmook Kang, Bennett Landman, Carissa Cascio, "Cortical morphology in autism: findings from a cortical shape-adaptive approach to local gyrification indexing", Cerebral Cortex, 2021.

Yucheng Tang, Riqiang Gao, Shizhong Han, Yunqiang Chen, Dashan Gao, Vishwesh Nath, Camilo Bermudez, Michael R Savona, Shunxing Bao, Ilwoo Lyu, Yuankai Huo, Bennett A Landman, "Body Part Regression with Self-supervision", IEEE Transactions on Medical Imaging (TMI), 2021.

Killian Hett, Ilwoo Lyu, Paula Trujillo Diaz, Alexander Lopez, Megan Aumann, Kathleen Larson, Peter Hedera, Benoit Dawant, Bennett Landman, Daniel Claassen, Ipek Oguz, "Anatomical texture patterns identify cerebellar distinctions between essential tremor and Parkinson's disease", Human Brain Mapping, 2021.

Ilwoo Lyu, Shunxing Bao, Lingyan Hao, Jewelia Yao, Jacob Miller, Willa Voorhies, Warren Taylor, Silvia Bunge, Kevin Weiner, Bennett Landman, "Labeling Lateral Prefrontal Sulci using Spherical Data Augmentation and Context-aware Training", NeuroImage, 2021.

Yucheng Tang, Riqiang Gao, Ho Hin Lee, Shizhong Han, Yunqiang Chen, Dashan Gao, Vishwesh Nath, Camilo Bermudez, Michael Savona, Richard Abramson, Shunxing Bao, Ilwoo Lyu, Yuankai Huo, Bennett Landman, "High-resolution 3D Abdominal Segmentation with Random Patch Network Fusion", Medical Image Analysis (MedIA), 2021.

Roza Bayrak, Colin Hansen, Jorge Salas, Nafis Ahmed, Ilwoo Lyu, Yuankai Huo, Catie Chang, “From Brain to Body: Learning Low‑Frequency Respiration and Cardiac Signals from fMRI Dynamics”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.

Shunxing Bao, Yucheng Tang, Ho Hin Lee, Riqiang Gao, Sophie Chiron, Ilwoo Lyu, Lori Coburn, Keith Wilson, Joseph Roland, Bennett Landman, Yuankai Huo, “Random Multi‑Channel Image Synthesis for Multiplexed Immunofluorescence Imaging”, MICCAI Workshop on Computational Pathology (COMPAY), 2021.

Yue Liu, Dario Englot, Victoria Morgan, Warren Taylor, Ying Wei, Ipek Oguz, Bennett Landman, Ilwoo Lyu, “Establishing Surface Correspondence for Post‑surgical Cortical Thickness Changes in Temporal Lobe Epilepsy”, SPIE Medical Imaging (SPIE), 2021.

Chang Yu, Yue Liu, Leon Cai, Cailey Kerley, Kaiwen Xu, Katherine Aboud, Warren Taylor, Hakmook Kang, Andrea Shafer, Lori Beason‑Held, Susan Resnick, Bennett Landman, Ilwoo Lyu, “Validation of group‑wise registration for surface‑based functional MRI analysis”, SPIE Medical Imaging (SPIE), 2021.

ByungOk Han, Woo-han Yun, Jang-hee Yoo, Won Hwa Kim, "Toward Unbiased Facial Expression Recognition in the Wild via Cross-dataset Adaptation'', IEEE Access, 2020. 

Gowtham Krishnan Murugesan, Chandan Ganesh, Sahil Nalawade, Elizabeth M. Davenport, Ben Wagner, Won Hwa Kim, Joseph A. Maldjian, "BrainNET: Inference of Brain Network Topology using Machine Learning", Brain Connectivity, 2020.  

Tuan Q. Dinh, Yunyang Xiongy, Zhichun Huangy, Tien Voy, Akshay Mishray, Won Hwa Kim, Sathya N. Ravi, Vikas Singh, "Performing Group Difference Testing on Graph Structured Data from GANs: Analysis and Applications in Neuroimaging", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020. 

Fan Yang, Amal Isaiah, Won Hwa Kim, "COVLET: Covariance-based Wavelet-like Transform for Statistical Analysis of Brain Characteristics in Children", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.  

Feng Tong*, Muhammad Shahid, Peng Jin, Sungyong Jung, Won Hwa Kim, Jayoung Kim "Classification of the Urinary Metabolome using Machine Learning and Potential Applications to Diagnosing Interstitial Cystitis", Bladder, 2020. [*: Feng advised by WHKim] 

Jayoung Kim, Peng Jin, Won Hwa Kim, Wun-Jae Kim "Utilizing Machine Learning to Discern Hidden Clinical Values from Big Data in Urology", Investigative and Clinical Urology, 2020. 

Xin Ma, Guorong Wu, Won Hwa Kim, "Multi-resolution Graph Neural Network for Identifying Disease-specific Variations in Brain Connectivity",  Annual Meeting of the Organization for Human Brain Mapping (OHBM) , 2020. 

Xin Ma, Guorong Wu, Won Hwa Kim, "Multi-resolution Graph Neural Network for Detecting Variations in Brain Connectivity",  Annual Meeting of the Organization for Human Brain Mapping (OHBM) , 2020. 

Xin Ma, Guorong Wu, Won Hwa Kim, "Enriching Statistical Inferences on Brain Connectivity for Alzheimer's Disease Analysis via Latent Space Graph Embedding", IEEE International Symposium on Biomedical Imaging (ISBI), 2020. [Accepted for Oral Presentation] 

Xin Ma, Guorong Wu, Won Hwa Kim, "Multi-resolution Graph Neural Network for Detecting Variations in Brain Connectivity", Interaction of Geometry and Topology in Biomedical Imaging (ISBI Workshop) , 2020. 

Anna Philips, Farah Naz, Kate Kyung Hyun, Vivek Patel, Gorden G. Zhang, Won Hwa Kim, "Social Media Text Analysis using Multi-kernel Convolution Neural Network for Ride Hailing Service Assessment", Transportation Research Board (TRB) Annual Meeting, 2020. 

Colin Hansen, Qi Yang, Ilwoo Lyu, Francois Rheault, Cailey Kerley, Bramsh Qamar Chandio, Shreyas Fadnavis, Owen Williams, Andrea Shafer, Susan Resnick, David Zald, Laurie Cutting, Warren Taylor, Brian Boyd, Eleftherios Garyfallidis, Adam Anderson, Maxime Descoteaux, Bennett Landman, Kurt Schilling, "Pandora: 4-D white matter bundle population-based atlases derived from diffusion MRI fiber tractography", Neuroinformatics, 2020.

Shih-Gu Huang, Ilwoo Lyu, Anqi Qiu, Moo Chung, "Fast Polynomial Approximation of Heat Kernel Convolution on Manifolds and Its Application to Brain Sulcal and Gyral Graph Pattern Analysis", IEEE Transactions on Medical Imaging (TMI), 2020.

Rui Wang, Kimberly Albert, Warren Taylor, Brian Boyd, Justin Blaber, Ilwoo Lyu, Bennett Landman, Jennifer Vega, Sepideh Shokouhi, Hakmook Kang, "A Bayesian Approach to Examining Default Mode Network Functional Connectivity and Cognitive Performance in Major Depressive Disorder", Psychiatry Research: Neuroimaging, 2020.

Aaron Tetreault, Tony Phan, Dana Orlando, Ilwoo Lyu, Hakmook Kang, Bennett Landman, Ryan Darby, "Network localization of clinical, cognitive, and neuropsychiatric symptoms in Alzheimer's disease", Brain, 2020.

Seongjae Hwang, Zirui Tao, Won Hwa Kim*, Vikas Singh*, "Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging" International Conference on Computer Vision (ICCV), 2019. (*: Senior authorship shared) 

Seongjae Hwang, Zirui Tao, Won Hwa Kim*, Vikas Singh*, "Statistical Analysis of Longitudinally and Conditionally Generated Neuroimaging Measures via Conditional Recurrent Flow", Statistical Deep Learning in Computer Vision (ICCV Workshop), 2019. (*: Senior authorship shared) 

Won Hwa Kim, Annie M. Racine, Nagesh Adluru, Seong Jae Hwang, Kaj Blennow, Henrik Zetterberg, Cynthia M.Carlsson, Sanjay Asthana, Rebecca L. Koscik, Sterling C. Johnson, Barbara B. Bendlin, Vikas Singh, "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, 2019. 

Annie M. Racine, Andrew P. Merluzzi, Nagesh Adluru, Derek Norton, Rebecca L. Koscik, Lindsay R. Clark, Sara E. Berman, Christopher R. Nicholas, Sanjay Asthana, Andrew L. Alexander, Kaj Blennow, Henrik Zetterberg, Won Hwa Kim, Vikas Singh, Cynthia M. Carlsson, Barbara B. Bendlin, Sterling C. Johnson, "Association of longitudinal whitematter degeneration and cerebrospinal fluid biomarkers of neurodegeneration, inflammation and Alzheimer's disease in late-middle-aged adults", Brain Imaging and Behavior, 2019. 

Seong Jae Hwang, Nagesh Adluru, Won Hwa Kim, Sterling C. Johnson, Barbara B. Bendlin, Vikas Singh, "Associations between PET Amyloid Pathology and DTI Brain Connectivity in Preclinical Alzheimer's Disease", Brain Connectivity, 2019. 

Vishwesh Nath, Kurt Schilling, Prasanna Parvathaneni, Colin Hansen, Allison Hainline, Yuankai Huo, Justin Blaber, Ilwoo Lyu, Vaibhav Janve, Yurui Gao, Iwona Stepniewska, Adam Anderson, Bennett Landman, "Deep Learning Reveals Untapped Information for Local White-matter Fiber Reconstruction in Diffusion-weighted MRI", Magnetic Resonance Imaging, 2019.

Ilwoo Lyu, Hakmook Kang, Neil Woodward, Martin Styner, Bennett Landman, "Hierarchical Spherical Deformation for Cortical Surface Registration", Medical Image Analysis (MedIA), 2019.

Prasanna Parvathaneni, Vishwesh Nath, Maureen McHugo, Yuankai Huo, Susan Resnick, Neil Woodward, Bennett Landman, Ilwoo Lyu, "Improving Human Cortical Sulcal Curve Labeling in Large Scale Cross-Sectional MRI using Deep Neural Networks", Journal of Neuroscience Methods, 2019.

Prasanna Parvathaneni, Ilwoo Lyu, Yuankai Huo, Baxter Rogers, Kurt Schilling, Vishwish Nath, Justin Blaber, Allison Hainline, Adam Anderson, Neil Woodward, Bennett Landman, "Improved Gray Matter Surface based Spatial Statistics in Neuroimaging Studies", Magnetic Resonance Imaging, 2019.

Shunxing Bao, Camilo Bermudez, Yuankai Huo, Prasanna Parvathaneni, William Rodriguez, Susan Resnick, Pierre-Francois D'Haese, Maureen McHugo, Stephan Heckers, Benoit Dawant, Ilwoo Lyu, Bennett Landman, "Registration-based Image Enhancement Improves Multi-Atlas Segmentation of the Thalamic Nuclei and Hippocampal Subfields", Magnetic Resonance Imaging, 2019.

Prasanna Parvathaneni, Shunxing Bao, Vishwesh Nath, Neil Woodward, Daniel Claassen, Carissa Cascio, David Zald, Yuankai Huo, Bennett Landman, Ilwoo Lyu, “Cortical Surface Parcellation using Spherical Convolutional Neural Networks”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.

Vishwesh Nath, Ilwoo Lyu, Kurt Schilling, Prasanna Parvathaneni, Colin Hansen, Yuankai Huo, Vaibhav Janve, Yurui Gao, Iwona Stepniewska, Adam Anderson, Bennett Landman, “Enabling Multi‑Shell b‑Value Generalizability of Data‑Driven Diffusion Models with Deep SHORE”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.

Shih‑Gu Huang, Ilwoo Lyu, Anqi Qiu, Moo Chung, “Fast Polynomial Approximation to Heat Diffusion in Manifolds”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.

Ilwoo Lyu, Sun Hyung Kim, Jessica Girault, John Gilmore, Martin Styner, "A Cortical Shape-Adaptive Approach to Local Gyrification Index", Medical Image Analysis (MedIA), 2018.

Ilwoo Lyu, Sun Hyung Kim, Neil Woodward, Martin Styner, Bennett Landman, "TRACE: A Topological Graph Representation for Automatic Sulcal Curve Extraction", IEEE Transactions on Medical Imaging (TMI), 2018.

Yuankai Huo, Justin Blaber, Stephen Damon, Brian Boyd, Shunxing Bao, Prasanna Parvathaneni, Camilo Bermudez Noguera, Shikha Chaganti, Vishwesh Nath, Jasmine Greer, Ilwoo Lyu, William French, Allen Newton, Baxter Rogers, Bennett Landman, "Towards Portable Large-Scale Image Processing with High-Performance Computing", Journal of Digital Imaging, 2018.

Shunxing Bao, Prasanna Parvathaneni, Yuankai Huo, Yogesh Barve, Andrew Plassard, Yuang Yao, Hongyang Sun, Ilwoo Lyu, David Zald, Bennett Landman, Aniruddha Gokhale, “Technology Enablers for Big Data, Multi‑Stage Analysis in Medical Image Processing”, IEEE International Conference on BigData (BigData), 2018.

Ilwoo Lyu, Martin Styner, Bennett Landman, “Hierarchical Spherical Deformation for Shape Correspondence”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018.

Vishwesh Nath, Kurt Schilling, Prasanna Parvathaneni, Colin Hansen, Allison Hainline, Camilo Bermudez, Samuel Remedios, Justin Blaber, Ilwoo Lyu, Vaibhav Janve, Yurui Gao, Iwona Stepniewska, Baxter Rogers, Allen Newton, Taylor Davis, Jeff Luci, Adam Anderson, Bennett Landman, “Inter‑Scanner Harmonization of High Angular Resolution DW‑MRI using Null Space Deep Learning”, MICCAI Workshop on Computational Diffusion MRI (CDMRI), 2018.

Prasanna Parvathaneni, Shunxing Bao, Allison Hainline, Yuankai Huo, Kurt Schilling, Hakmook Kang, Owen Williams, Neil Woodward, Susan Resnick, David Zald, Ilwoo Lyu, Bennett Landman, “Harmonization of White and Gray Matter Features in Diffusion Microarchitecture for Cross Sectional Studies”, International Conference on Clinical and Medical Image Analysis (ICCMIA), 2018.

Meg Bobo, Shunxing Bao, Yuankai Huo, Yuang Yao, Jack Virostko, Andrew Plassard, Ilwoo Lyu, Albert Assad, Richard Abramson, Bennett Landman, “Fully Convolutional Neural Networks Improve Abdominal Organ Segmentation”, SPIE Medical Imaging (SPIE), 2018.

Vishwesh Nath, Kurt Schilling, Allison Hainline, Prasanna Parvathaneni, Justin Blaber, Ilwoo Lyu, Adam Anderson, Hakmook Kang, Allen Newton, Baxter Rogers, Bennett Landman, “SHARD: Spherical Harmonic based Robust Outlier Detection for HARDI Methods”, SPIE Medical Imaging (SPIE), 2018.

Shunxing Bao, Yuankai Huo, Prasanna Parvathaneni, Andrew Plassard, Camilo Bermudez, Yuang Yao, Ilwoo Lyu, Aniruddha Gokhale, Bennett Landman, “A Data Colocation Grid Framework for Big Data Medical Image Processing – Backend Design”, SPIE Medical Imaging (SPIE), 2018.

Prasanna Parvathaneni, Ilwoo Lyu, Yuankai Huo, Justin Blaber, Allison Hainline, Hakmook Kang, Neil Woodward, Bennett Landman, “Constructing Statistically Unbiased Cortical Surface Templates Using Feature‑Space Covariance”, SPIE Medical Imaging (SPIE), 2018.

Ilwoo Lyu, Hakmook Kang, Neil Woodward, Bennett Landman, “Sulcal Depth‑based Cortical Shape Analysis in Normal Healthy Control and Schizophrenia Groups”, SPIE Medical Imaging (SPIE), 2018.

Won Hwa Kim, "A Multi-resolution Framework for Statistical Analysis of Neuroimaging Data" Doctoral Thesis, 2017. 

Won Hwa Kim, Seongjae Hwang, Nagesh Adluru, Sterling C. Johnson, Vikas Singh, " Graph Completion: A Generalization of Netflix Prize Problem to Designing Cost Effective Neuroimaging Trials in Preclinical AD", Alzheimer's Association International Conference (AAIC), 2017. 

Won Hwa Kim, Mona Jalal, Seongjae Hwang, Sterling C. Johnson, Vikas Singh, "Online Graph Completion: Multivariate Signal Recovery in Computer Vision", Computer Vision and Pattern Recognition (CVPR), 2017. 

Won Hwa Kim, Seong Jae Hwang, Nagesh Adluru, Sterling C. Johnson, Vikas Singh, "Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging", European Conference on Computer Vision (ECCV), 2016. 

Seong Jae Hwang, Won Hwa Kim, Barbara B. Bendlin, Nagesh Adluru, Vikas Singh, "Multi-Resolution Analysis of DTI-Derived Brain Connectivity and the Influence of PET-Derived Alzheimer's Disease Pathology in a Preclinical Cohort", Alzheimer's Association International Conference (AAIC), 2016. 

Won Hwa Kim*, Hyunwoo J. Kim*, Nagesh Adluru, Vikas Singh, "Latent Variable Graphical Model Selection using Harmonic Analysis: Applications to the Human Connectome Project (HCP)", Computer Vision and Pattern Recognition (CVPR), 2016. [Spotlight / Acceptance rate: 9.7%]

*: First authorship shared. 

Won Hwa Kim, Sathya Ravi, Sterling C. Johnson, Ozioma Okonkwo, Vikas Singh, "On Statistical Analysis of Neuroimages with Imperfect Registration", International Conference on Computer Vision (ICCV), 2015. 

Won Hwa Kim, Nagesh Adluru, Moo K. Chung, Ozioma C. Okonkwo, Sterling C. Johnson, Barbara B. Bedlin, Vikas Singh, "Multi-resolution Statistical Analysis of Brain Connectivity Graphs in Preclinical Alzheimer’s Disease", NeuroImage, 2015. 

Won Hwa Kim, Nagesh Adluru, Moo K. Chung, Ozioma C. Okonkwo, Sterling C. Johnson, Barbara B. Bedlin, Vikas Singh, "Multi-resolution Statistical Analysis of Brain Connectivity Graphs in Preclinical Alzheimer’s Disease", Alzheimer's Association International Conference (AAIC), 2015. 

Won Hwa Kim, Barbara B. Bendlin, Moo K. Chung, Sterling C. Johnson, Vikas Singh, "Statistical Inference Models for Image Datasets with Systematic Variations", Computer Vision and Pattern Recognition (CVPR), 2015. 

Won Hwa Kim, Vikas Singh, Moo K. Chung, Nagesh Adluru, Barbara B. Bendlin, Sterling C. Johnson, "Multi-resolution statistical analysis on graph structured data in Neuroimaging", International Symposium on Biomedical Imaging (ISBI), 2015 (Invited paper / Oral presentation) 

Ilwoo Lyu, Sun Hyung Kim, Joon-Kyung Seong, Sang Wook Yoo, Alan Evans, Yundi Shi, Mar Sanchez, Marc Niethammer, Martin Styner, "Robust Estimation of Group-wise Cortical Correspondence with an Application to Macaque and Human Neuroimaging Studies", Frontiers in Neuroscience, 2015.

Won Hwa Kim, Vikas Singh, Moo K. Chung, Chris Hinrichs, Deepti Pachauri, Ozioma C. Okonkwo, Sterling C. Johnson, "Multi-resolutional Shape Features via non-Euclidean Wavelets: Applications to Statistical Analysis of Cortical Thickness", NeuroImage, 2014. 

A. Pasha Hosseinbor, Won Hwa Kim, Nagesh Adluru, Amit Acharya, Houri K. Vorperian, Moo. K. Chung, "The 4D Hyperspherical Diffusion Wavelet: a New Method for the Detection of Localized Anatomical Variation", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2014. 

Won Hwa Kim, Nagesh Adluru, Moo K. Chung, Sylvia Charchut, Johnson J. GadElkarim, Lori Altshuler, Teena Moody, Anand Kumar, Vikas Singh, and Alex D. Leow, "Multi-resolutional Brain Network Filtering and Analysis via Wavelets on Non-Euclidean Space", Medical Image Computing and Computer Assisted Intervention (MICCAI), 2013.

Manasi Datar, Ilwoo Lyu, Sun Hyung Kim, Joshua Cates, Martin Styner, Ross Whitaker, “Geodesic Distances to Landmarks for Dense Correspondence on Ensembles of Complex Shapes”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2013.

Joohwi Lee, Ilwoo Lyu, Ipek Oguz, Martin Styner, “Particle‑Guided Image Registration”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2013.

Won Hwa Kim, Moo K. Chung, Vikas Singh, "Multi-resolution Shape Analysis via Non-Euclidean Wavelets: Applications to Mesh Segmentation and Surface Alignment Problems", Computer Vision and Pattern Recognition (CVPR), 2013.

Ilwoo Lyu, Sun Hyung Kim, Joon‑Kyung Seong, Sang Wook Yoo, Alan Evans, Yundi Shi, Mar Sanchez, Marc Niethammer, Martin Styner, “Cortical Correspondence via Sulcal Curve‑Constrained Spherical Registration with Application to Macaque Studies”, SPIE Medical Imaging (SPIE), 2013.

Won Hwa Kim, Deepti Pachauri, Charles Hatt, Moo K. Chung, Sterling C. Johnson, Vikas Singh, "Wavelet Based Multi-scale Shape Features on Arbitrary Surfaces for Cortical Thickness Discrimination", Advances in Neural Information Processing Systems (NIPS), 2012.

Won Hwa Kim, Jeong Woo Park, Woo Hyun Kim, Wong Hyong Lee, Myung Jin Chung, "Proposal of 2D Mood Model for Human-like Behaviors of Robot", The Journal of Korea Robotics Society, 2010.

Won Hwa Kim, Jeong Woo Park, Won Hyong Lee, Woo Hyun Kim, Myung Jin Chung, " Stochastic Approach on a Simplified OCC Model for Uncertainty and Believability", International Conference on Computational Intelligence in Robotics and Automation (CIRA), 2009.

Jeongwoo Park, Won Hwa Kim, Wong Hyong Lee, Myung Jin Chung, "A Robot Simulator'FRESi'for Dynamic Facial Expression", International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), 2009.

Jeongwoo Park, Woo Hyun Kim, Wong Hyong Lee, Won Hwa Kim, Myung Jin Chung, "Lifelike Facial Expression of Mascot-type Robot based on Emotional Boundaries", Robotics and Biomimetics (ROBIO), 2009.

Yubin Han, Hayoung Ahn, Won Hwa Kim, "Optimizing Convolutional Neural Network Embedding Space:  A Model Utilizing Statistical Loss Function", Korea Computer Congress (KCC), 2024. 

Minjae Jeong, Hyuna Cho, Sungyoon Jung, Won Hwa Kim, "Uncertainty-aware Diffusion-based Adversarial Attack for Realistic Colonoscopy Image Synthesis", Korea Computer Congress (KCC), 2024. 

Yujee Song, Donghyun Lee, Rui Meng, Won Hwa Kim, "Explainable and Continuous Time Modeling of Marked Temporal Point Process", Workshop on Image Processing and Image Understanding (IPIU), 2024. 

Jaeyoon Sim, Sooyeon Jeon, Yubin Han, Won Hwa Kim, "Learning to Approximate Adaptive Kernel Convolution on Graphs", Workshop on Image Processing and Image Understanding (IPIU), 2024. [Bronze Award] 

Hyuna Cho, Injun Choi, Yechan Hwang, Suha Kwak, Won Hwa Kim, "Interactive Network Perturbation for Semi-Supervised Semantic Segmentation", Workshop on Image Processing and Image Understanding (IPIU), 2023. [Oral Presentation / Silver Award] 

Hyuna Cho, Yubin Han, Guorong Wu, Won Hwa Kim, "Spatio-Temporal Multi-Layer Perceptron for Longitudinal Human Brain Connectome Analysis", Workshop on Image Processing and Image Understanding (IPIU), 2023. [Oral Presentation / Bronze Award] 

Ellen Jieun Oh, Taegeun Choi, Geunyoung Lee, Won Hwa Kim, "Unpaired Retina Image Enhancement using Wavelet Scattering Transfom", Workshop on Image Processing and Image Understanding (IPIU), 2023. [Encouragement Award]