Younjoon Chung
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I am a Research Associate at the Human Sensing Lab at Carnegie Mellon University.
My research interests lie in the intersection of machine learning, computer vision and healthcare.
Specifically, I focus on developing responsible AI systems towards equitable healthcare.
Previously, I was an M.S. in Computer Vision (MSCV) student in the Robotics Institute at Carnegie Mellon University, advised by Prof. Fernando De la Torre.
Before CMU, I was a research engineer at VUNO Inc., where I developed algorithms for mobile digital radiography devices and computer-aided detection (CADe) systems.
I also worked on various medical imaging projects with Prof. Yoon-Chul Kim at Samsung Medical Center.
In my free time, I enjoy making contributions to open-source projects, playing tennis, and watching baseball.
I led the official Korean translation of the Keras documentation project,
and have over 25+ commits merged in the Keras ecosystem.
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Recent Highlights
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My paper "Domain Gap Embeddings for Generative Dataset Augmentation" has been accepted to CVPR 2024. |
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Joined CMU School of Computer Science, Robotics Institute as a Research Associate, Spring 2024. |
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Graduated from CMU M.S. in Computer Vision in Dec 2023, advised by Prof. Fernando De la Torre. |
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Submitted a paper in CVPR 2024, Nov 2024. Fingers crossed! |
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Published a paper in Physica Medica, with Prof. Yoon-Chul-Kim, Nov 2023. [Link] |
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Joined CMU as an M.S. in Computer Vision student, Aug 2022. |
Publications
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Domain Gap Embeddings for Generative Dataset Augmentation
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Younjoon Chung*, Oliver Wang*, Chen Wu, Fernando De la Torre
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| CVPR 2024 |
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Few-shot, fine-tuning free pipeline for targeted dataset generation.
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Deep learning for classification of late gadolinium
enhancement lesions based on the 16-segment left ventricular model
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Yoon-Chul Kim, Younjoon Chung, Yeon Hyeon Choe
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| Physica Medica (2023) |
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Segmental analysis of myocardial late gadolinium enhancement (LGE) lesions.
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Automatic localization of anatomical landmarks
in cardiac MR Perfusion using random forests
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Yoon-Chul Kim, Younjoon Chung, Yeon Hyeon Choe
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| Biomedical Signal Processing and Control (2017) |
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Learning-based approach to distinguish landmarks and non-landmarks for LV center and RV insertion point.
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EVCMR: A tool for the quantitative evaluation and visualization of cardiac
MRI data
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Yoon-Chul Kim, Khu Rai Kim, Kwanghee Choi, Minwoo Kim, Younjoon Chung, Yeon Hyeon Choe
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| Computers in Biology and Medicine (2019) |
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Open-source CMR post-processing tool for evaluating cardiac MRI data.
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Patents
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Method to read chest image
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Beomhee Park, Minki Chung, Seo Taek Kong, Younjoon Chung
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U.S. Patent Application 17/466,697, filed March 10, 2022.
| | The method includes: determining whether or not to identify presence of cardiomegaly for a
chest image; detecting a lung region and a heart region respectively, and calculating a cardiothoracic
ratio of the chest image using the detected lung region and the detected heart region. |
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Method for detecting abnormal findings and generating interpretation text of medical image
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Minki Chung, Beomhee Park, Seo Taek Kong, Younjoon Chung
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U.S. Patent Application 17/471,001, filed March 17, 2022.
| | The method includes: generating anatomical location information for the one or more lesions using an anatomical analysis model,
and generating a diagnosis result for the received body medical image. |
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Miscellaneous
- Mentor, CMU Undergraduate AI Mentoring Program (Fall 2023, Spring 2024)
- Committee Member, Keras Korea (Mar 2018 - Present)
- Technology Evangelist, Microsoft Student Partners (Mar 2015 - Mar 2016)
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| Template adopted from: 1 and 2
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