Yeseul Cho
About Me
Hi! I am an AI Engineer Intern at Nota AI. I received my master’s degree from the Kim Jaechul Graduate School of AI at KAIST, where I was fortunate to be advised by Chulhee Yun.
My research interests broadly lie in understanding and improving the training of modern neural networks, particularly large language models. My previous work has focused on data selection, and I have also explored problems involving the adaptation and modification of trained models, including model merging and machine unlearning.
Going forward, I am interested in understanding how training data shapes optimization dynamics. In particular, I am interested in how the amount and timing of high-quality data affect language model pre-training, and how the efficiency and behavior of different optimizers change with batch size and training scale.
Research Interests
- Data-Efficient Deep Learning
- Model Adaptation
- Optimization
Education
- M.S. in Artificial Intelligence, Korea Advanced Institute of Science and Technology, Sep. 2024 - Aug. 2026
- B.S. in Biomedical Engineering, Korea University, Mar. 2020 - Aug. 2024
News
- [Aug. 2026] I joined Nota AI as an AI Engineer Intern.
- [Aug. 2026] I received my M.S. in Artificial Intelligence from KAIST.
- [May. 2025] Our paper on dataset pruning under supervised learning is accepted to ICML 2025
Publications
(* denotes equal contribution)
-
ICML 2026 Workshop on High-dimensional Learning Dynamics (HiLD)
-
ICML 2025ICLR 2025 Workshop on Navigating and Addressing Data Problems for Foundation Models (DataFM)
