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Dr. Chun has moved on to Sungkyunkwan University.  Please visit his home page for current information and contact info. 


Curriculum Vitae

Il Yong Chun received the B.Eng. degree from Korea University in 2009, and the Ph.D. degree from Purdue University in 2015, both in electrical and computer engineering.
He joined the Department of Electrical and Computer Engineering at the University of Hawaii, Manoa (UHM) in 2019 as an Assistant Professor. Prior to joining UHM, he was a Postdoctoral Research Associate in Mathematics, Purdue University, and a Research Fellow in Electrical Engineering and Computer Science, the University of Michigan, from 2015-2016 and 2016-2019, respectively.

My research interests in data science include
  • machine learning & AI (e.g., self-supervised learning, iterative neural networks, and sparse representation learning),
  • optimization (e.g., non-convex optimization, block optimization, and proximal gradient methods), and
  • compressed sensing (e.g., multi-imager/sensor system and sampling optimization),
with current and past projects in imaging, image processing, and computer vision:
  • medical imaging (e.g., X-ray CT, MRI, PET, and SPECT),
  • computational photography (e.g., light-field photography, depth estimation, and 3D object tracking),
  • vision-based autonomous systems (e.g., end-to-end autonomous driving, visual SLAM, inter-vehicle distance estimation, anomaly detection using drone imaging), and
  • biomedical image computing (e.g., abnormality detection on brain images and microscopic image segmentation).
I am interested both in developing computational data science solutions to these problems, as well as improving fundamental understanding of these solutions. For a snapshot of our current research, see recent preprints/submitted papers under the "publications" link on the left-hand menu and available projects under the ECE's BME and SDS research links.

I have been teaching the following imaging and data science courses at UHM:
  • EE416: Introduction to Image Processing and Computer Vision (F19, F20), and
  • EE616: Computational Image Processing and Computer Vision (S20, S21).