Blog - Hyungjin

๐Ÿ“š Welcome to my Homepage

Welcome to my personal homepage. I am an ongoing Ph.D. student @KAIST. The motivation of my research is “Making invisible, visible”. Mostly, I work on solving inverse problems arising in computational imaging, and I focus on using deep learning, especially unsupervised learning methods to accomplish it. Unlike many works in literature that simply adopt published methods off-the-shelf, I also try to delve on theoretical links of machine learning and signal processing.

Hyungjin Chung

Hyungjin Chung

Ph.D. student - Deep Learning & Inverse Problems

Korea Advanced Institute of Science and Technology (KAIST) BISPL

Biography

Hyungjin Chung is a Ph.D. student @KAIST bio-imaging signal processing & learning lab (BISPL). His research interests include, but is not restricted to solving inverse problems via deep learning. He has published papers and ongoing projects in a wide variety of fields including compressed sensing MRI (CS-MRI), tomographic reconstruction, microscopy, and phase retrieval.

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Interests
  • Deep Learning
  • Computational Imaging
  • Inverse Problems
Education

  • MS in Bio & Brain Engineering, 2021

    Korea Advanced Institute of Science & Technology (KAIST)

  • BS in Biomedical Engineering, 2019

    Korea University

Recent Posts

Law of Total Expectation
Law of Total Expectation PRML์˜ 74pg. Bayesian statistics์— ๋Œ€ํ•œ ์„ค๋ช… ์ค‘ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์ˆ˜์‹์ด ๋‚˜์˜จ๋‹ค. $$ \mathbb{E}{\theta}[\theta] = \mathbb{E}{\mathcal{D}}[\mathbb{E}_{\theta}[\theta|\mathcal{D}]] $$ ์ด ์‹์˜ ์ง๊ด€์ ์ธ ์˜๋ฏธ๊ฐ€ ์™€ ๋‹ฟ์ง€ ์•Š์•˜์–ด์„œ, ์ด ํฌ์ŠคํŠธ๋ฅผ ํ†ตํ•ด ์ •๋ฆฌํ•œ๋‹ค.
Hyungjin Chung
Last updated on Mar 10, 2021 3 min read Math
Elastic Distortion
Data augmentation Dataset์˜ ์–‘์ด ์ ์€ ๊ฒฝ์šฐ, data augmentation์€ classification, semantic segmentation๋“ฑ์˜ task์˜ accuracy๋ฅผ ์˜ฌ๋ฆฌ๋Š” ๋ฐ์— ๋„์›€์ด ๋ฉ๋‹ˆ๋‹ค. ํŠนํžˆ๋‚˜ Biomedical ๋ถ„์•ผ์™€ ๊ฐ™์ด ํ•„์—ฐ์ ์œผ๋กœ ๋ฐฉ๋Œ€ํ•œ ์–‘์˜ ๋ฐ์ดํ„ฐ๋ฅผ ์–ป๊ธฐ ํž˜๋“  ์ƒํ™ฉ์—์„œ๋Š” ์–ด์ฉ” ์ˆ˜ ์—†์ด ์ด๋Ÿฐ data augmentation์— ๊ธฐ๋Œ€์„œ ์กฐ๊ธˆ์ด๋ผ๋„ accuracy๋ฅผ ์˜ฌ๋ ค์•ผ ํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ์ผ๋ฐ˜์ ์ž…๋‹ˆ๋‹ค.
Hyungjin Chung
Last updated on Mar 10, 2021 5 min read Augmentation
Elastic Distortion

Projects

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Probabilistic Machine Learning - Kevin Murphy
Brief summary, guidance, and solutions to the famous machine-learning bible “Probabilistic Machine Learning” in Korean.
Probabilistic Machine Learning - Kevin Murphy

News

Hyungjin Chung
Apr 27, 2021 12:00 AM
Interview at BRIC
Interview at BRIC

Interview at BRIC for the publication of “Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Data” in Medical Image Analysis, 2021.

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Hyungjin Chung
Mar 21, 2021 12:00 AM
Nature Machine Intelligence Cover selected
Nature Machine Intelligence Cover selected

The paper I have co-authored, link is featured as the cover of the March issue in Nature Machine Intelligence

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Recent Publications

Yoseob Han, Jaeduck Jang, Eunju Cha, Junho Lee, Hyungjin Chung, Myoungho Jeong, Tae-Gon Kim, Byeong Gyu Chae, Hee Goo Kim, Shinae Jun, Sungwoo Hwang, Eunha Lee, Jong Chul Ye (2021). Deep learning STEM-EDX tomography of nanocrystals. In Nat. Mach. Int..

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Joon Yeul Nam, Hyungjin Chung, Kyu Sung Choi, Hyuk Lee, Seung Jun Han, Tae Jun Kim, Hosim Soh, Eun Kang, Soo_jeong Cho, Jong Chul Ye, Jong Pil Im, Sang Gyun Kim, Yoon Jun Kim, Joo Sung Kim, Jung-Hwan Yoo, Hyunsoo Chung, Jeong-Hoon Lee (2021). A Deep Learning Model for Diagnosing Gastric Mucosal Lesions Using Endoscopic Images: Development, Validation, and Method Comparison. in SSRN.

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Gyutaek Oh, Byeongsu Sim, Hyungjin Chung, Leonard Sunwoo, Jong Chul Ye (2020). Unpaired deep learning for accelerated MRI using optimal transport driven cycleGAN. IEEE TCI.

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Eunju Cha, Hyungjin Chung, Eung Yeop Kim, Jong Chul Ye (2020). Unpaired training of deep learning tMRA for flexible spatio-temporal resolution. IEEE TMI.

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Hyungjin Chung, Jong Chul Ye (2020). Feature Disentanglement in generating three-dimensional structure from two-dimensional slice with sliceGAN. In ArXiv.

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Hyungjin Chung, Jaehyun Kim, Jeong Hee Yoon, Jeong Min Lee, Jong Chul Ye (2020). Simultaneous super-resolution and motion artifact removal in diffusion-weighted MRI using unsupervised deep learning. In ArXiv.

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Hyungjin Chung, Eunju Cha, Leonard Sunwoo, Jong Chul Ye (2020). Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Data. In Medical Image Analysis.

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Joonhyung Lee, Hyunjong Kim, Hyungjin Chung, Jong Chul Ye (2020). Deep Learning Fast MRI Using Channel Attention in Magnitude Domain. IEEE ISBI.

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Hyungjin Chung, Jaeyoung Huh, Geon Kim, Yong Keun Park, Jong Chul Ye (2020). Missing Cone Artifacts Removal in ODT using Unsupervised Deep Learning in Projection Domain. In IEEE TCI.

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Popular Topics

AdaIN Attention Augmentation Book classification Deep Learning DWI endoscopy Feature disentanglement Math Microscopy Motion artifact correction MRI Optical Diffraction Tomography Optimal Transport Projection Discriminator SliceGAN Super resolution Unsupervised Learning

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