I am a Ph.D. student at ALIN-LAB, advised by Prof. Jinwoo Shin at Korea Advanced Institute of Science and Technology (KAIST).
My research interests focus on trustworthy machine learning for real-world deployment. I mainly focus on robust learning schemes for handling distributional shifts, e.g., out-of-distribution, adversarial examples, and natural corruptions. However, I also have a broad interest in the interpretability and the transparency of deep networks.
Contact: jihoontack at kaist.ac.kr
Publications
(C: Conference, W: Workshop, P: Preprint, *: Equal contribution)
[P1] Consistency Regularization for Adversarial Robustness
Jihoon Tack, Sihyun Yu, Jongheon Jeong, Minseon Kim, Sung Ju Hwang, Jinwoo Shin
[paper] [code][C2] CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
Jihoon Tack*, Sangwoo Mo*, Jongheon Jeong, Jinwoo Shin
Neural Information Processing Systems (NeurIPS) 2020
Qualcomm Innovation Fellowship Korea 2020
[paper] [code] [slide] [poster][C1] Adversarial Self-Supervised Contrastive Learning
Minseon Kim, Jihoon Tack, Sung Ju Hwang
Neural Information Processing Systems (NeurIPS) 2020
[paper] [code] [site]
Education
- M.S. & Ph.D. integrated course in Artificial Intelligence, Korea Advanced Institute of Science and Technology (KAIST), 2020 - present (advisor: Prof. Jinwoo Shin)
- M.S. in Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 2019 - 2020 (advisor: Prof. Jinwoo Shin)
- B.S. in Electrical Engineering and Mathematics (minored), Korea Advanced Institute of Science and Technology (KAIST), 2014 - 2019
Honor & Award
- Qualcomm Innovation Fellowship Korea 2020
- Top reviewer award (top 10%), NeurIPS 2020
Academic Services
- Conference reviewer
- NeurIPS 2020, 2021
- ICML 2021 (expert)
- CVPR 2021
- ICCV 2021
- Journal reviewer
- IEEE Transactions on Neural Networks and Learning Systems
Invited Talks
- “CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances”
- @ Qualcomm AI Research: Qualcomm Innovation Fellowship Winner Talk, Feb 2021
- @ NeurIPS Social: ML in Korea, Dec 2020
- @ Korea Software Congress (KSC): Korea Post-NeurIPS-2020 Workshop, Dec 2020
Teaching
- TA, AI602: Recent Advances in Deep Learning, KAIST Spring 2021
- TA, AI504: Programming for AI, KAIST Fall 2020
- TA, AI-Expert Program, Samsung-DS Summer 2020
- TA, AI703: Systems and Applications of AI and ML, KAIST Spring 2020
- TA, EE209: Programming Structure for Electrical Engineering, KAIST Fall 2019
Project
- Interpretable ML for object detection, 2020 - present
- Used car project, KB Capital, 2017 - 2020
Building an AI system that predicts price, depreciation, and sales duration of the used car.
Currently, my system is deployed at KBchachacha service (only Korean supported).