Daeun Yun

A novel method for micropollutant quantification using deep learning and multi-objective optimization.

Daeho Kang, K. Cho, Sang-Soo Baek, 2022, Water research.

Developing a deep learning model for the simulation of micro-pollutants in a watershed

K. Cho, Mayzonee Ligaray, Sang-Soo Baek, 2021, Journal of Cleaner Production.

Characterization of micropollutants in urban stormwater using high-resolution monitoring and machine learning.

Daeho Kang, K. Cho, Sang-Soo Baek, 2023, Water research.

Simulation models of microbial community, pH, and volatile fatty acids of anaerobic digestion developed by machine learning

Ather Abbas, Juhee Shin, Sung Il Yu, 2024, Journal of Water Process Engineering.

Spatiotemporal estimation of groundwater and surface water conditions by integrating deep learning and physics-based watershed models

Sang-Soo Baek, J. Pyo, Soobin Kim, 2024, Water research X.

Profiling emerging micropollutants in urban stormwater runoff using suspect and non-target screening via high-resolution mass spectrometry.

Sang-Soo Baek, Junho Jeon, Daeun Yun, 2024, Chemosphere.

Enhancing flow rate prediction of the Chao Phraya River Basin using SWAT–LSTM model coupling

S. Chotpantarat, Daeun Yun, Heewon Jeong, 2024, Journal of Hydrology: Regional Studies.