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Seong Jae Hwang
Seong Jae Hwang Assistant Professor

Biography

Dr. Seong Jae Hwang received his B.S. in Computer Science from the University of Illinois at Urbana-Champaign in 2011, M.S.E. in Robotics from the University of Pennsylvania in 2013, and Ph.D. in Computer Sciences from the University of Wisconsin-Madison in 2019. He joined the Department of Computer Science in the School of Computing and Information at the University of Pittsburgh in 2019.

His research is focused on developing statistical machine learning and deep neural network methods for analyzing imaging modalities in computer vision, machine learning, and medical imaging. On the technical side, he develops algorithms for cross-sectional and sequential data from small to large scales with statistical machine learning and deep learning models. On the application side, his interests range from neuroscientific discoveries including understanding the pathological progression of Alzheimer’s disease to machine learning/computer vision applications.

Research Interests

Medical imaging analysis for neurodegenerative diseases
Computer vision / Machine learning / Deep learning

Recent Publications

Seong Jae Hwang, Zirui Tao, Won Hwa Kim, Vikas Singh, “Statistical Analysis of Longitudinally and Conditionally Generated Longitudinal Neuroimaging Measures via Conditional Recurrent Flow”, The First Workshop on Statistical Deep Learning in Computer Vision, International Conference on Computer Vision (ICCV), 2019.

Seong Jae 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.

Seong Jae Hwang, Ronak R. Mehta, Hyunwoo J. Kim, Vikas Singh, “Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging”, Conference on Uncertainty in Artificial Intelligence (UAI), 2019.

Seong Jae Hwang, Joonseok Lee, Balakrishnan Varadarajan, Zheng Xu, Ariel Gordon and Apostol (Paul) Natsev, “Large-Scale Training Framework for Video Annotation”, Conference on Knowledge Discovery and Data Mining (KDD), 2019.

Courtney A. Miller, Seong Jae Hwang, Meghan M. Cotter, Houri K. Vorperian, “Cervical vertebral growth and emergence of sexual dimorphism: A developmental study using computed tomography”, Journal of Anatomy, 2019.

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, 2018.

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, 2018.

Seong Jae Hwang, Sathya N. Ravi, Zirui Tao, Hyunwoo J. Kim, Maxwell D. Collins, Vikas Singh, “Tensorize, Factorize and Regularize: Robust Visual Relationship Learning”, Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

Won Hwa Kim, Mona Jalal, Seong Jae Hwang, Sterling C. Johnson, Vikas Singh, “Online Graph Completion: Multivariate Signal Recovery in Computer Vision”, Conference on 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, Nagesh Adluru, Maxwell D. Collins, Sathya N. Ravi, Barbara B. Bendlin, Sterling C. Johnson, Vikas Singh, “Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks”, Conference on Computer Vision and Pattern Recognition (CVPR), 2016.

Seong Jae Hwang, Maxwell D. Collins, Sathya N. Ravi, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson, Vikas Singh, “A Projection Free Method for Generalized Eigenvalue Problems with a Nonsmooth Regularizer”, International Conference on Computer Vision (ICCV), 2015.