A deep learning researcher. My research interests include theoretical analysis of deep neural networks, computer vision, and machine learning.
Visiting Researcher | Osaka University, Japan **January 2024 - Present
Graduate School of Information Science and Technology
Advisor: Yoshinobu Kawahara (mls.ist.osaka-u.ac.jp)
Ph.D. | Pohang University of Science and Technology (POSTECH), South Korea **February 2020 - February 2025
Department of Electrical Engineering
Advisor: Sang Woo Kim (icsl.postech.ac.kr)
M.S. | Pohang University of Science and Technology (POSTECH), South Korea **February 2018 - February 2020
Department of Electrical Engineering
Advisor: Sang Woo Kim (icsl.postech.ac.kr)
B.S. | Pohang University of Science and Technology (POSTECH), South Korea February 2014 - February 2018
Department of Electrical Engineering
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Reviewer
AISTATS (2023)
NeurIPS (2024)
Expert Systems With Applications (2020, 2023)
Neural Networks (2024)
Applied Soft Computing (2024)
EURASIP Journal on Image and Video Processing (2024)
International Journal of Data Science and Analytics (2024)
Teaching Assistant
EECE276 Electrical Engineering Lab (2019, 2021, 2022, 2023)
DISU399 Next Generation Semiconductor Innovation (2022)
Scholarship
Korea Student Aid Foundation (KOSAF), The National Scholarship for Science and Engineering
Full Undergraduate Scholarship (2014.03-2018.02)
Oral Presentations on Domestic Conference
POSTECH-NAVER AI DAY (2022)
ICS (2019)
CICS(2019, 2020)
ICESI (2022)
KIEE Summer Conference (2023)
Languages
English: Fluent
Japanese: Native
Korean: Native
Industry-Academia Cooperation Projects
Samsung Advanced Institute of Technology, Autonomous Vehicles Team, Project Leader (Main), 2019-2024, Grant Number: IO201210-08019-01.
Korea Electric Power Corporation, Project Assistant (Sub), 2018-2021, Grant Number: R18XA06-21.
POSCO Research Institute, Project Assistant (Sub), 2018-2019.
Patents
ELECTRONIC DEVICE AND OPERATING METHOD OF ELECTRONIC DEVICE, Attorney Ref No. 8947-001769-US, 2022-09-21, USA Patents, Under Review.
Programming Skills
General Deep-learning Libraries: Python, PyTorch, TensorFlow, NumPy, Scikit-learn, timm, HuggingFace, and OpenMMLab. Specific Deep-learning Libraries: ONNX and TensorRT for model acceleration, Slurm for experiments on cluster environment. Linux: I live in terminal. I enjoy lots of customization with Vim, Tmux, Zsh, iTerm2, etc. Intermediate: C, C++, MATLAB, R, Java.
