AISys Lab. ECE, Seoul National University
member portrait Hyeyoon Lee PhD Student
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I am a Ph.D. student in the Department of Electrical and Computer Engineering at Seoul National University. I am interested in building safe and efficient AI, where the applications include building adversarially robust AI, and accelerating heavy generative AI.

Publication

FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic
FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic
Kanghyun Choi, Hyeyoon Lee, SunJong Park, Dain Kwon, Jinho Lee
Neural Information Processing Systems (NeurIPS)   ·   Dec 2025
GitHub
Top Conf. AI/ML
DANCE++: Differentiable Accelerator/Network Co-Exploration with Hard Constraints and Data-Free Training for Real-World Scenarios
DANCE++: Differentiable Accelerator/Network Co-Exploration with Hard Constraints and Data-Free Training for Real-World Scenarios
Kanghyun Choi, Deokki Hong, Hyeyoon Lee, Joonsang Yu, Noseong Park, Youngsok Kim, Jinho Lee
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD)   ·   Jun 2025
Paper
SCI AI/ML Arch.
MimiQ: Low-Bit Data-Free Quantization of Vision Transformers with Encouraging Inter-Head Attention Similarity
MimiQ: Low-Bit Data-Free Quantization of Vision Transformers with Encouraging Inter-Head Attention Similarity
Kanghyun Choi, Hyeyoon Lee, Dain Kwon, SunJong Park, Kyuyeun Kim, Noseong Park, Jonghyun Choi, Jinho Lee
AAAI Conference on Artificial Intelligence (AAAI)   ·   Feb 2025
ArXiv
GitHub
Slide
Poster
Top Conf. AI/ML
DataFreeShield: Defending Adversarial Attacks without Training Data
DataFreeShield: Defending Adversarial Attacks without Training Data
Hyeyoon Lee, Kanghyun Choi, Dain Kwon, SunJong Park, Mayoore Selvarasa Jaiswal, Noseong Park, Jonghyun Choi, Jinho Lee
International Conference on Machine Learning (ICML)   ·   May 2024
Top Conf. AI/ML
Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators
Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators
Mingi Yoo1, Jaeyong Song1, Hye Yoon Lee, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee
PACT (Best Paper Award)   ·   Oct 2022
ArXiv
Paper
Top Conf. Arch. AI/ML
Deep Composer Classification Using Symbolic Representation
Deep Composer Classification Using Symbolic Representation
Sunghyeon Kim1, Hyeyoon Lee1, Sunjong Park1, Jinho Lee, Keunwoo Choi
LBD@ISMIR   ·   Oct 2020
Paper
ArXiv
Poster
AI/ML
Enabling Hard Constraints in Differentiable Neural Network and Accelerator Co-Exploration
Enabling Hard Constraints in Differentiable Neural Network and Accelerator Co-Exploration
Deokki Hong, Kanghyun Choi, Hye Yoon Lee, Joonsang Yu, Noseong Park, Youngsok Kim, Jinho Lee
Design Automation Conference (DAC)   ·   Jan 2023
ArXiv
Top Conf. AI/ML Arch.
It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher
It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher
Kanghyun Choi, Hye Yoon Lee, Deokki Hong, Joonsang Yu, Noseong Park, Youngsok Kim, Jinho Lee
Computer Vision and Pattern Recognition Conference (CVPR)   ·   Apr 2022
ArXiv
Slide
GitHub
Top Conf. AI/ML
Fast Adversarial Training with Dynamic Batch-level Attack Control
Fast Adversarial Training with Dynamic Batch-level Attack Control
Jaewon Jung, Jaeyong Song, Hongsun Jang, Hyeyoon Lee, Kanghyun Choi, Noseong Park, Jinho Lee
Design Automation Conference (DAC)   ·   Jul 2023
Top Conf. AI/ML

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