Hankook Lee

hankook.lee at skku.edu / Github / Google Scholar

I am an assistant professor in Department of Computer Science and Engineering at Sungkyunkwan University (SKKU). Prior to this, I worked at LG AI Research as a Research Scientist and Korea Advanced Institute of Science and Technology (KAIST) as a Postdoctoral Researcher. I completed my Ph.D. degree in the School of Electrical Engineering at KAIST, advised by Prof. Jinwoo Shin.

I am interested in improving the efficiency of deep learning. Specifically, my research has focused on data-efficient deep learning, including self-supervised learning, few-shot learning, and transfer learning. I am also interested in solving real-world problems on various data domains such as computer vision, chemistry, and tabular data.

Efficient Learning Lab (ELL) at SKKU. I am currently looking for self-motivated graduate students and undergraduate interns with a strong interest in the area of deep learning. If you are interested in joining our lab, send me an email with your transcript and CV.

Publications

J: Journal / C: Conference / W: Workshop / *: equal contribution

[C15] Learning Equi-angular Representations for Online Continual Learning
Minhyuk Seo, Hyunseo Koh, Wonje Jeung, Min Jae Lee, San Kim, Hankook Lee, Sungjun Cho, Sungik Choi, Hyunwoo Kim, Jonghyun Choi
Conference on Computer Vision and Pattern Recognition (CVPR), 2024
[J1/W] Few-shot Anomaly Detection via Personalization
Sangkyung Kwak, Jongheon Jeong, Hankook Lee, Woohyuck Kim, Dongho Seo, Woojin Yun, Wonjin Lee, Jinwoo Shin
IEEE Access, 2024
ICML Workshop on New Frontiers in Adversarial Machine Learning (AdvML-Frontiers), 2023
[paper]
[C14] Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models
Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee
Neural Information Processing Systems (NeurIPS), 2023
[paper]
[W3] Diffusion-based Semantic-Discrepant Outlier Generation for Out-of-Distribution Detection
Suhee Yoon*, Sanghyu Yoon*, Hankook Lee, Sangjun Han, Ye Seul Sim, Kyungeun Lee, Hyeseung Cho, Woohyung Lim
NeurIPS Workshop on Synthetic Data Generation with Generative AI (SyntheticData4ML), 2023
[paper]
[W2] Mixed-Curvature Transformers for Graph Representation Learning
Sungjun Cho, Seunghyuk Cho, Sungwoo Park, Hankook Lee, Honglak Lee, Moontae Lee
ICML Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), 2023
[paper]
[W1] Fragment-based Multi-view Molecular Contrastive Learning
Seojin Kim*, Jaehyun Nam*, Junsu Kim, Hankook Lee, Sungsoo Ahn, Jinwoo Shin
ICLR Workshop on Machine Learning for Materials (ML4Materials), 2023
[paper]
[C13/W] Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck
Jongheon Jeong, Sihyun Yu, Hankook Lee, Jinwoo Shin
Computer Vision and Pattern Recognition (CVPR), 2023
ECCV Workshop on Out-of-distribution Generalization in Computer Vision (ECCVW-OOD-CV), 2022
[paper] [arxiv]
[C12/W] STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables
Jaehyun Nam, Jihoon Tack, Kyungmin Lee, Hankook Lee, Jinwoo Shin
International Conference on Learning Representations (ICLR), Spotlight presentation, 2023
Neural Information Processing Systems Workshop on Table Representation Learning (NeurIPSW-TRL), 2022
Samsung Humantech Paper Awards, Bronze Prize, 2023
[paper] [code]
[C11/W] Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning
Huiwon Jang*, Hankook Lee*, Jinwoo Shin
International Conference on Learning Representations (ICLR), Spotlight presentation, 2023
Neural Information Processing Systems Workshop on Meta-Learning (NeurIPSW-MetaLearn), 2022
[paper] [arxiv] [code]
[C10/W] Guiding Energy-based Models via Contrastive Latent Variables
Hankook Lee, Jongheon Jeong, Sejun Park, Jinwoo Shin
International Conference on Learning Representations (ICLR), Spotlight presentation, 2023
Neural Information Processing Systems Workshop on Self-Supervised Learning (NeurIPSW-SSL), Oral Presentation, 2022
[paper] [arxiv] [code]
[C9] Meta-Learning with Self-Improving Momentum Target
Jihoon Tack, Jongjin Park, Hankook Lee, Jaeho Lee, Jinwoo Shin
Neural Information Processing Systems (NeurIPS), 2022
[paper] [arxiv] [slide] [poster] [code]
[C8] Patch-level Representation Learning for Self-supervised Vision Transformers
Sukmin Yun, Hankook Lee, Jaehyung Kim, Jinwoo Shin
Computer Vision and Pattern Recognition (CVPR), Oral Presentation, 2022
[paper] [arxiv] [poster] [code]
[C7/W] Improving Transferability of Representations via Augmentation-Aware Self-Supervision
Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin
Neural Information Processing Systems (NeurIPS), 2021
ICML 2021 Workshop: Self-Supervised Learning for Reasoning and Perception
[paper] [arxiv] [slide] [poster] [code]
[C6] Self-Improved Retrosynthetic Planning
Junsu Kim, Sungsoo Ahn, Hankook Lee, Jinwoo Shin
International Conference on Machine Learning (ICML), 2021
[paper] [arxiv] [slide] [poster] [code]
[C5/W] RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning
Hankook Lee, Sungsoo Ahn, Seung-Woo Seo, You Young Song, Eunho Yang, Sung Ju Hwang, Jinwoo Shin
International Joint Conference on Artificial Intelligence (IJCAI), 2021
NeurIPS Workshop for Machine Learning for Molecules, 2020
[paper] [arxiv (long version)] [slide] [poster] [code]
[C4] GTA: Graph Truncated Attention for Retrosynthesis
Seung-Woo Seo*, You Young Song*, June Yong Yang, Seohui Bae, Hankook Lee, Jinwoo Shin, Sung Ju Hwang, Eunho Yang
AAAI Conference on Artificial Intelligence (AAAI), 2021
[paper]
[C3] Guiding Deep Molecular Optimization with Genetic Exploration
Sungsoo Ahn, Junsu Kim, Hankook Lee, Jinwoo Shin
Neural Information Processing Systems (NeurIPS), 2020
[paper] [arxiv] [code]
[C2] Self-supervised Label Augmentation via Input Transformations
Hankook Lee, Sung Ju Hwang, Jinwoo Shin
International Conference on Machine Learning (ICML), 2020
Qualcomm-KAIST Innovation Awards, 2019
[paper] [arxiv] [code] [talk]
[C1] Learning What and Where to Transfer
Yunhun Jang*, Hankook Lee*, Sung Ju Hwang, Jinwoo Shin
International Conference on Machine Learning (ICML), 2019
[paper] [arxiv] [code] [slide] [talk 55:14~59:09]

Work Experience

Sungkyunkwan University
Suwon, South Korea, 2024. 03 - present
Assistant Professor
LG AI Research
Seoul, South Korea, 2023. 02 - 2024. 02
Research Scientist
Korea Advanced Institute of Science and Technology (KAIST)
Seongnam, South Korea, 2022. 09 - 2023. 02
Postdoctoral Researcher
Samsung Advanced Institute of Technology (SAIT)
Suwon, South Korea, 2020. 01 - 2020. 03
Visiting Student
Frograms Inc. (changed to Watcha Inc. @ 2018)
Seoul, South Korea, 2013. 08 - 2014. 12
Research and Development Engineer

Education

Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, South Korea, 2016. 03 - 2022. 08
M.S. & Ph.D. in Electrical Engineering (advisor: Jinwoo Shin)
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, South Korea, 2010. 02 - 2016. 02
B.S. in Mathematical Science and Computer Science (double major)

Awards

  • Qualcomm-KAIST Innovation Awards (2019)
  • International Collegiate Programming Contest (ICPC)
    • Asia Daejeon Regional: Grand Prize (1st place, 2012), Gold Prize (2nd place, 2010)
    • Participated in ICPC World Finals 2013
  • Korea Olympiad in Informatics (KOI) : Gold Prize (2009)

Services

  • Area Chair
    • NeurIPS (2024)
  • Reviewer
    • Conferences: ICLR (2020-2024), NeurIPS (2020-2023), ICML (2021-2024), AAAI (2022-2024)
    • Conference Workshops: Self-supervised Learning (ICML 2021, NeurIPS 2021-2022, ECCV 2022)
    • Journals: ACM ToMPECS, IEEE TPAMI, Journal of Machine Learning Research (JMLR), Nature Communications