Hankook Lee

hankook.lee at kaist.ac.kr
Algorithmic Intelligence Lab, KAIST, Daejeon, South Korea.


I am currently on the job market!

I am a Ph.D. candidate in the School of Electrical Engineering at Korea Advanced Institute of Science and Technology (KAIST), advised by Prof. Jinwoo Shin. My research has investigated how to learn deep neural networks with limited human prior knowledge. Specifically, my interests include self-supervised learning, transfer learning, data augmentation, and real-world applications with limited labels.

Publications

(* equal contribution)

Guiding Energy-based Models via Contrastive Latent Variables
Hankook Lee, Jongheon Jeong, Sejun Park, Jinwoo Shin
under review, 2022
Meta-Learning with Self-Improving Momentum Target
Jihoon Tack, Jongjin Park, Hankook Lee, Jaeho Lee, Jinwoo Shin
under review, 2022
Learning Robust Representations via Nuisance-extended Information Bottleneck
Jongheon Jeong, Sihyun Yu, Hankook Lee, Jinwoo Shin
under review, 2022
FragCL: Fragmentation-Based Contrastive Learning for Molecule Representation
Seojin Kim, Jaehyun Nam, Junsu Kim, Hankook Lee, Sungsoo Ahn, Jinwoo Shin
under review, 2022
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]
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]
Self-Improved Retrosynthetic Planning
Junsu Kim, Sungsoo Ahn, Hankook Lee, Jinwoo Shin
International Conference on Machine Learning (ICML), 2021
[paper] [arxiv] [slide] [poster] [code]
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]
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]
Guiding Deep Molecular Optimization with Genetic Exploration
Sungsoo Ahn, Junsu Kim, Hankook Lee, Jinwoo Shin
Neural Information Processing Systems (NeurIPS), 2020
[paper] [arxiv] [code]
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]
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]
Anytime Neural Prediction via Slicing Networks Vertically
Hankook Lee, Jinwoo Shin
arXiv, 2018
[arxiv] [code]

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)

Work Experience

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

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

  • Conference Reviewer
    • ICLR (2020, 2021, 2022)
    • NeurIPS (2020, 2021, 2022)
    • ICML (2021, 2022)
    • AAAI (2022)
    • Self-supervised Learning Workshops (ICML 2021, NeurIPS 2021, ECCV 2022)
  • Journal Reviewer
    • ACM ToMPECS
    • IEEE TPAMI