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, microscopic image segmentation, and dental radiographs classification), and
  • "autonomous systems" (e.g., end-to-end autonomous driving and 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 UH:
  • EE416: Introduction to Image Processing and Computer Vision (F19, F20), and
  • EE616: Computational Image Processing and Computer Vision (S20, S21).

Group Highlights in 2020:
20-12, Dr. Chun has been awarded the Ingeborg v.F. McKee Fund of the Hawaiʻi Community Foundation for self-supervised deep learning for high-quality low-dose X-ray CT.
20-08, UH News featured an article about my state-of-the-art iterative AI system (recently published online in IEEE Trans. Pattern Anal. Mach. Intell., the most prestigious AI and computer vision journal (IF '20: 19.420)): AI innovation may improve COVID-19 diagnosis.
20-07, Emerging Technology Ventures (ETV) and the Chun's imaging and data science group created an industry-academia partnership. I look forward to solving big challenges together and developing cutting-edge "autonomous systems"/AI technologies with ETV!
20-05, UH CoE wrote an article on my graduate course EE616: Computational Image Processing and Computer Vision of which final project, dental image diagnostics, is partnered with Hawaiʻi Dental Service: Engineering students develop real-world solutions through industry-integrated courses. See also UH News. I am proud that many students successfully completed EE616 coursework in S2020 that has unprecedented challenges due to COVID-19!
20-02, UH News wrote a news article on our recent light-field photography work using transparent photodetectors and advanced data science solution (published in Nature Photonics (2-yr. IF: 31.583)): Engineering professor’s 3D camera improves research in Hawaiʻi.

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