Ji Hwan Park
Ji Hwan Park

Ji Hwan Park is an assistant professor in the School of Computer Science at the University of Oklahoma (OU). Before joining OU, he was an assistant computational scientist at Brookhaven National Lab. He earned his Ph.D. under prof. Arie Kaufman at Stony Brook University. His research interests are visual analytics, data visualization (including VR/AR), machine learning/deep learning, and human computer interaction.

Curriculum Vitae, Google Scholar

Prospective students:

I am seeking graduate (MS/PhD) students at CS@OU. If you are interested in data visualization (including VR/AR), visual analytics, machine learning/deep learning, human-computer interation, and data science, please contact me with your resume.

News

  • 04/2021: Our paper Feature Importance in a Deep Learning Climate Emulator has been accepted to AIMOCC workshop co-held with ICLR.
  • 11/2020: Our paper In Situ Compression Artifact Removal in Scientific Data Using Deep Transfer Learning and Experience Replay has been accepted to Machine Learning: Science and Technology.
  • 02/2020: Our paper Machine learning prediction of incidence of Alzheimer's disease using large-scale administrative health data has been accepted to npj Digital Medicine.
  • 12/2019: Our paper Efficient and Effective Graph Convolution Networks will be presented at SIAM Int'l. Conference on Data Mining (SDM) 2020!
  • 11/2019: Our paper CMed: Crowd Analytics for Medical Imaging Data has been accepted to IEEE Trans. Visualization and Computer Graphics!

Projects

Aesthetically Pleasing Charts for Casual Information Visualization

Graphoto: a framework that automatically generates a photo or adjusts an existing one to match a line graph. More INFO

Ji Hwan Park, Arie Kaufman, and Klaus Mueller, "Graphoto: Aesthetically Pleasing Charts for Casual Information Visualization", IEEE Computer Graphics and Application, 2019

Saliency-Aware Compression

A transfer-function-guided 3D blockbased saliency-aware compression scheme for volumetric data that is both content- and spatially-scalable. More INFO

Ji Hwan Park, Ievgeniia Gutenko, and Arie Kaufman, "Transfer Function-Guided Saliency-Aware Compression for Transmitting Volumetric Data", IEEE Transaction on Multimedia (accepted)

Crowd Consensus Analytics for Virtual Colonoscopy

C2A: a visual analytic framework to help clinical technicians obtain the best results from a crowdsourced VC application More INFO

Ji Hwan Park, Seyedkoosha Mirhosseini, Saad Nadeem, Joseph Marino, Arie Kaufman, Kevin Baker, and Matthew Barish, "Crowdsourcing for Identification of Polyp-Free Segments in Virtual Colonoscopy Videos", SPIE Medical Imaging, 101380V, 2017 (oral presentation)

Ji Hwan Park, Saad Nadeem, Seyedkoosha Mirhosseini, and Arie Kaufman, "C2A: Crowd Consensus Analytics for Virtual Colonoscopy", IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 21-30, 2016

Turning Digital Photos into Ambient Visualizations

ambienizer
Ambienizer: a visual encoding approach that seeks to convey a user's personal data in a casual non-technical way

Ji Hwan Park, Arie Kaufman, and Klaus Mueller,"Photo Visualization: Representation of Data in a Photo", CEWIT International Conference, 2013

Crowd Analytics for Medical Imaging Data

CMed: a visual analytic framework to allow crowdsourcing application analysts/developers to observe patterns and gather insights into the crowdsourced medical data More INFO

Ji Hwan Park, Saad Nadeem, Saeed Boor Boor, Joseph Marino, and Arie Kaufman, "CMed: Crowd Analytics for Medical Imaging Data", to be appeared in IEEE Transactions on Visualization and Computer Graphics, 2019

Ji Hwan Park, Saad Nadeem, Joseph Marino, Kevin Baker, Matthew Barish, and Arie Kaufman, "Crowd-Assisted Polyp Annotation of VirtualColonoscopy Videos", SPIE Medical Imaging 2018 (oral presentation)

Exploration of Spatio-Temporal Data

geobrick
GeoBrick: a visual framework to explore multivariate spatio-temporal data for domain experts

Ji Hwan Park, Saad Nadeem, and Arie Kaufman, "GeoBrick: Exploration of Spatio-Temporal Data", The Visual Computer, 2018

Recent Publications

Sandeep Madireddy, Ji Hwan Park, Sunwoo Lee, Prasanna Balaprakash, Shinjae Yoo, Wei-keng Liao, Cory D. Hauck, M. Paul Laiu, Richard Archibald, "In Situ Compression Artifact Removal in Scientific Data Using Deep Transfer Learning and Experience Replay", to be appeared in Machine Learning: Science and Technology, 2020

Ji Hwan Park, Han Eol Cho, Jong Hun Kim, Melanie Wall, Yaakov Stern, Hynsun Lim, Shinjae Yoo, Hyoung-Seop Kim, Jiook Cha, "Machine learning prediction of incidence of Alzheimer's disease using large-scale administrative health data", npj Digital Medicine, 3, 46, 2020

Siwu Liu, Ji Hwan Park, and Shinjae Yoo, "Efficient and Effective Graph Convolution Networks", SIAM International Conference on Data Mining 2020 (accepted)

Ji Hwan Park, Saad Nadeem, Saeed Boorboor, Joseph Marino, and Arie Kaufman, "CMed: Crowd Analytics for Medical Imaging Data", to be appeared in IEEE Transactions on Visualization and Computer Graphics, 2019

Ji Hwan Park, Shinjae Yoo, and Balu Nadiga, "Machine learning climate variability", Machine Learning and the Physical Sciences Workshop at NeurIPS 2019

Yun Wang, Chenxiao Xu, Ji-Hwan Park, Seonjoo Lee, Yaakov Stern, Shinjae Yoo, Jong Hun Kim, Hyoung Seop Kim, Jiook Cha, The Alzheimer's Disease Neuro imaging Initiative, "Diagnosis and prognosis of Alzheimer's disease using brain morphometry and white matter connectomes," NeuroImage: Clinical Vol.23, 101859, 2019

Ji Hwan Park, Saad Nadeem, and Arie Kaufman, "GeoBrick: Exploration of Spatio-Temporal Data", The Visual Computer, 35(2), pp 191�204, 2018

Ji Hwan Park, Saad Nadeem, Joseph Marino, Kevin Baker, Matthew Barish, and Arie Kaufman, "Crowd-Assisted Polyp Annotation of Virtual Colonoscopy Videos", SPIE Medical Imaging, 105790M, 2018 (oral presentation)

Saeed Boorboor, Saad Nadeem, Ji Hwan Park, Kevin Baker, Arie Kaufman, "Crowdsourcing Lung Nodules Detection and Annotation", SPIE Medical Imaging, 105791D, 2018

Ji Hwan Park, Ievgeniia Gutenko, and Arie Kaufman, "Transfer Function-Guided Saliency-Aware Compression for Transmitting Volumetric Data", to be appeared in IEEE Transaction on Multimedia, 2019

Ji Hwan Park, Arie Kaufman, and Klaus Mueller, "Graphoto: Aesthetically Pleasing Charts for Casual Information Visualization", IEEE Computer Graphics and Application, 38(6), pp 67-82, 2018

Ji Hwan Park, Seyedkoosha Mirhosseini, Saad Nadeem, Joseph Marino, Arie Kaufman, Kevin Baker, and Matthew Barish, "Crowdsourcing for Identification of Polyp-Free Segments in Virtual Colonoscopy Videos�, SPIE Medical Imaging, 101380V, 2017 (oral presentation)

Ji Hwan Park, Saad Nadeem, Seyedkoosha Mirhosseini, and Arie Kaufman, "C2A: Crowd Consensus Analytics for Virtual Colonoscopy" IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 21-30, 2016