Ph.D. student
Laboratory : Applied Artificial Intelligence Lab
Advisor : Prof. Il-Chul Moon
Institution : Korea Advanced Institute of Science and Technology (KAIST)
Contact me
cat2507 [at] kaist [dot] ac [dot] kr // baeheesun96 [at] gmail [dot] com
Research Interest
Machine Learning; Representation Learning
Generalization with Distribution Shift
Learning with noisy label
Domain Generalization
Publication (* denotes the equal contribution. )
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning (International Conference on Learning Representation (ICLR 2024), Vienna, Austria, May 07-11, 2024)
Heesun Bae, Seungjae Shin, Byeonghu Na and Il-Chul Moon
Unknown Domain Inconsistency Minimization for Domain Generalization (International Conference on Learning Representation (ICLR 2024), Vienna, Austria, May 07-11, 2024)
Seungjae Shin*, Heesun Bae*, Byeonghu Na, Yoon-yeong Kim, Il-Chul Moon
Label-Noise Robust Diffusion Models (International Conference on Learning Representation (ICLR 2024), Vienna, Austria, May 07-11, 2024)
Byeonghu Na, Yeongmin Kim, HeeSun Bae, Jung Hyun Lee, Se Jung Kwon, Wanmo Kang, Il-Chul Moon
Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior (AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feb 20-27, 2024)
Youngjae Cho, HeeSun Bae, Seungjae Shin, YeoDong Youn, Weonyoung Joo, and Il-chul Moon
Loss Curvature Matching for Dataset Selection and Condensation (International Conference on Artificial Intelligence and Statistics (AISTATS 23), Valencia, Spain, Apr 25-27, 2023)
Seungjae Shin*, Heesun Bae*, DongHyeok Shin, Weonyoung Joo, Il-Chul Moon
From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model (International Conference on Machine Learning (ICML) 2022)
HeeSun Bae*, Seungjae Shin*, Byeonghu Na, JoonHo Jang, Kyungwoo Song, Il-Chul Moon
Improving Group-based Robustness and Calibration via Ordered Risk and Confidence Regularization (Workshop on Spurious Correlations, Invariance, and Stability on International Conference on Machine Learning (ICML-SCIS) 2022)
Seungjae Shin, Byeonghu Na, HeeSun Bae, JoonHo Jang, Hyemi Kim, Kyungwoo Song, Youngjae Cho, Il-Chul Moon
Seungjae Shin*, Heesun Bae*, Giwoon Kim, Youngsoon Cho, Dongwook Lee, Donggil Jeong, HyunJoon Kim, Hyunjung Lee, Hyungjun Moon
Education
Ph.D. Candidate in Industrial Engineering, KAIST, Daejeon, Korea (advisor: Prof. Il-Chul Moon) (2022.03 - present)
M.S. in Industrial Engineering, KAIST, Daejeon, Korea (advisor: Prof. Il-Chul Moon) (2020.03 - 2022.02)
B.S. in Industrial Engineering, KAIST, Daejeon, Korea (2015.03 - 2020.02)
Experience
Research Internship, NAVER(2023.08~2023.11)
Exchange Student, Industral Engineeering (wirtschaftsingenieurwesen), Technische Universität Berlin (TUB) (2018.03 ~2018.08)
Awards
Winner, Qualcomm Innovation Fellowship Korea 2023
Winner, Qualcomm Innovation Fellowship Korea 2022
IE Frontier, Excellence prize, KAIST, 2017
Academic Services
Conference Reviewer
ICML(2023, 2024), NeurIPS(2022, 2023), ICLR(2024), AISTATS(2023)
last update: 18th, Jan, 2024