University of Hawaii

Electrical Engineering

Il Yong Chun

Assistant Professor

Office: POST 205H

Tel: (808) 956-5174


Personal Home Page

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 engineering.
He joined the Department of Electrical Engineering at the University of Hawaiʻi, Mānoa (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. During his Ph.D., he worked with Intel Labs, Samsung Advanced Institute of Technology, and Neuroscience Research Institute, as a Research Intern or a Visiting Lecturer.

My research interests in data science include

  • machine learning & AI (e.g., unsupervised/self-supervised learning, fast AI system training, and "big data"),
  • 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 & analysis, 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),
  • biomedical image computing (e.g., abnormality detection on brain images and microscopic image segmentation), and
  • vision-based autonomous systems (e.g., end-to-end autonomous driving, visual SLAM, inter-vehicle distance estimation, anomaly detection using drone imaging).
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.

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).

Group Highlights in 2021:
21-03, arXiv paper on deep vision-based inter-vehicle estimation (collab. w/ Muhyun and Dr. Hwang) is available. Great job, Muhyun!

***Click here to see further group news.***