gloom I am an Assistant Professor in the Department of Computer Science at the University of Pittsburgh. Before, I was at the University of Wisconsin - Madison under Vikas Singh.

[CV] [Google scholar]

My research interests are
- Medical imaging analysis (MRI, PET, DTI) for neurodegenerative disease (e.g., Alzheimer's disease)
- Computer vision and machine learning applications (e.g., video classification, sequence prediction, uncertainty estimation)
- Deep learning methods (e.g., sequential neural networks, generative models)

I am looking for motivated students.
If you are interested, please send me an email to [sjh95 (at) pitt.edu]


Spring 2020: CS 3710 - Advanced Topics in Artificial Intelligence

I will be teaching CS 3710 - Advanced Topics in Artificial Intelligence for Spring 2020.
This will an introductory course to medical imaging analysis and intro-intermediate for techniques in computer vision and machine learning. Various deep learning techniques (e.g., CNN, RNN, GAN) wil be covered and applied to computer vision and medical imaging datasets. No background in medical imaging will be necessary. Programming in MATLAB/Python and deep learning frameworks (e.g., TensorFlow, Pytorch) will be required.

Recent Work [ICCV 2019]: Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging


Recent Work [UAI 2019]: Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging

Ground Truth

Model Prediction
(Mean)

Model Uncertainty
(Variance)


Recent Work with Google Research [KDD 2019]: Large-Scale Training Framework for Video Annotation


News

Oct. 2019: Joining as an Assistant Professor in the Department of Computer Science at the University of Pittsburgh
Aug. 2019: Accepted for an Oral Presentation at The First Workshop on Statistical Deep Learning in Computer Vision (ICCV 2019), Seoul, Korea.
Jul. 2019: Accepted to ICCV 2019, Seoul, Korea.
May 2019: Accepted to UAI 2019, Tel Aviv, Israel.
Summer 2019: Internship at Google AI with Hanhan Li, Mountain View, USA.
Apr. 2019: Accepted for an Oral at KDD 2019, Anchorage, USA.
Mar. 2019: 3 Abstracts Accepted to AAIC 2019, Los Angeles, USA.
Feb. 2019: Accepted to Journal of Anatomy on "Cervical vertebral body growth and emergence of sexual dimorphism: A developmental study using computed tomography"
Oct. 2018: Accepted to NeuroImage: Clinical on "Cerebrospinal fluid biomarkers of neurofibrillary tangles and synaptic dysfunction are associated with longitudinal decline in white matter connectivity: A multi-resolution graph analysis"
Sept. 2018: Accepted to Brain Connectivity on "Associations between PET Amyloid Pathology and DTI Brain Connectivity in Preclinical Alzheimer's Disease"
Summer 2018: Internship at Google Research / Google AI with Joonseok Lee, Mountain View, USA.
Apr. 2018: Accepted to AAIC 2018, Chicago, USA.
Feb. 2018: Accepted to CVPR 2018, Salt Lake City, USA.
Apr. 2017: Accepted to AAIC 2017, London, England.
Mar. 2017: Accepted to CVPR 2017, Honolulu, USA.
Jul. 2016: Added new code: [MATLAB Toolbox] High quality fiber tract 3D visualization (soon available)
Jul. 2016: Accepted to ECCV 2016, Amsterdam, the Netherlands.
Mar. 2016: Accepted to AAIC 2016, Toronto, Canada. (oral)
Feb. 2016: Accepted to CVPR 2016, Las Vegas, USA.
Aug. 2015: Accepted to ICCV 2015, Santiago, Chile.

Publications (Conferences / Journals / Preprints)

2019

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

Seong Jae Hwang, Zirui Tao, Won Hwa Kim, Vikas Singh, "Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuromaging", International Conference on Computer Vision (ICCV), 2019. [Acceptance rate: 25%]
[pdf] [poster]

Seong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Sterling C. Johnson, 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. [Acceptance rate: 26%]
[pdf]

Seong Jae Hwang, Joonseok Lee, Balakrishnan Varadarajan, Ariel Gordon, Zheng Xu, Paul Natsev, "Large-Scale Training Framework for Video Annotation", Conference on Knowledge Discovery and Data Mining (KDD), 2019. [Oral acceptance rate: 9.2%] [Oral]
[pdf]

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.

2018

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, "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. [NeuroImage: Clinical]

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.
[Brain Connectivity] [Full article to be available soon]

Seong Jae Hwang, Sathya N. Ravi, Zirui Tao, Hyunwoo J. Kim, Maxwell D. Collins, Vikas Singh, "Tensorize, Factorize and Regularize: Robust Visual Relationship Learning", Computer Vision and Pattern Recognition (CVPR), 2018. [Acceptance rate: 29.7%]
[pdf]

2017

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

2016

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. [Acceptance rate: 26.6%]
[pdf] [supplementary]

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", Computer Vision and Pattern Recognition (CVPR), 2016. [Acceptance rate: 29.9%]
[pdf] [supplementary] [poster] [code will be available here] [project page]

2015

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 Problem with a nonsmooth Regularizer", International Conference on Computer Vision (ICCV), 2015. [Acceptance rate: 30.9%]
[pdf] [fixed eq (18),(20)] [supplementary] [poster] [code] [project page] [PubMed]

Conference Abstracts

2019

Seong Jae Hwang, Rebecca L. Koscik, Tobey J. Betthauser, Zirui Tao, Won Hwa Kim, Sterling C. Johnson, Vikas Singh, "Predicting amyloid accumulation trajectories in a risk-enriched Alzheimer's disease cohort with Deep Conditional Neural Networks", Alzheimer's Association International Conference (AAIC), 2019.

Zirui Tao, Ronak R. Mehta, Seong Jae Hwang, Rebecca L. Koscik, Erin Jonaitis, Sterling C. Johnson, Vikas Singh, "A Normative Modeling Based Analysis of Amyloid, Cognition, and Tau in Preclinical Alzheimer's Disease", Alzheimer's Association International Conference (AAIC), 2019.

Xingjian Zhen, Rudrasis Chakraborty, Nocholas Vogt, Seong Jae Hwang, Sterling C. Johnson, Barbara B. Bendlin, Vikas Singh, "Sequential Deep Learning Algorithms show structural connectivity differences by amyloid status", Alzheimer's Association International Conference (AAIC), 2019.

2018

Seong Jae Hwang, Sathya N. Ravi, Nagesh Adluru, Barbara B. Bendlin, Sterling C. Johnson, Vikas Singh, "Data-Driven Propagation Modeling of PET-Derived Alzheimer's Pathology in a Preclinical Cohort", Alzheimer's Association International Conference (AAIC), 2018.

2017

Won Hwa Kim, Seong Jae 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.

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. [Oral]

Patents

Won Hwa Kim, Seong Jae Hwang, Nagesh Adluru, Sterling Johnson, Vikas Singh, "Computerized System for Efficient Augmentation of Data Sets", 2018, US20180113990A1
[Google Patents]

Zheng Han, Xiaowei Dai, Seong Jae Hwang, Jason Fass, "Fast object tracking framework for sports video recognition", 2016, US9449230B2
[Google Patents]