🙋🏻‍♀️Personal Information

Ph.D student (Advisor: Taesup Moon)

Machine Intelligence and Data Science Lab (M.IN.D Lab)

Department of Electrical and Computer Engineering

Seoul National University

Contact

email [email protected] / [email protected]

github https://github.com/sangwon79

💡 Research Interests

• AI Trustworthy
  • Fairness, AI Alignment
  • Model bias / shortcut learning ****
  • Reinforcement learning with human feedback
• Continual Learning

🎓 Education

• Ph.D course [2022.03 ~] (Advisor : Taesup Moon)
  • Department of Electrical and Computer Engineering, Seoul National University (SNU)
• M.S. [2018.09 ~2022.02] (Advisor : Taesup Moon)
  • Department of Electrical and Computer Engineering, SungKyunKwan University (SKKU)
• B.S. [2012.03 ~ 2018.08]
  • Department of Mathematics / Computer Engineering, SungKyunKwan University (SKKU)

📄 Publications

Preprint

Conference paper

• [C8]  Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? – A Theoretical and Empirical Study

  Sangwon Jung,* Sumin Yu, Sanghyuk Chun and Taesup Moon

  • Neural Information Processing Systems (NeurIPS), Dataset and Benchmark Track, 2024

• [C7] Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline

  Donggyu Lee*, Sangwon Jung* and Taesup Moon

  • International Conference on Learning Representations (ICLR), 2024
  • AAAI 2023 Bridge Program on Continual Causality

• [C6] Re-weighting based Group Fairness Regularization via Classwise Robust Optimization

  Sangwon Jung*, Taeeon Park, Sanghyuk Chun and Taesup Moon

  • International Conference on Learning Representations (ICLR), 2023

• [C5] Data Condensation with Contrastive Signals

  Saehyung Lee, Sanghyuk Chun, Sangwon Jung, Sangdoo Yun, and Sungroh Yoon

  • International Conference on Machine Learning (ICML), 2022