Introduce
I am a fifth-year MS/Ph.D student in electrical and computer engineering (ECE) at Seoul National University (SNU), advised by Prof. Se Young Chun. I earned my B.S degree in electrical and computer engineering (ECE) from Seoul National University (SNU).
Research Interests
My research interests lie in \textbf{efficient generative AI}: making generative models resource-, computation-, and parameter-efficient across every stage of development and deployment, and validating these efficiency claims on real, constrained hardware rather than relying on algorithmic metrics alone. While I am interested in both Natural Language Processing (NLP) and Computer Vision (CV), my current focus is on generative vision models, particularly diffusion-based image and video generation. Specifically, my research explores, but is not limited to, the following areas:
- Efficient Deep Learning
- Hardware-aware Model Compression
- On-device Learning and Adaptation
Researches
Harmonization for a black-box deep learning model
ISMRM 2025 (Oral, Summa cum laude)
Minjun Kim, Hwihun Jeong, Hoigi Seo, Wongi Jeong, Juhyung Park, Se Young Chun, Jongho Lee
Fully Quantized Always-on Face Detector Considering Mobile Image Sensors [arXiv]
ICCVW 2023 (Oral)
Haechang Lee*, Wongi Jeong*, Dongil Ryu*, Hyunwoo Je, Albert No, Kijeong Kim**, Se Young Chun** (*co-first, **co-corresponding)