NEWS
(2023-06) NEW PAPER ALERT!
Heesoo's latest research "Effects of spatiotemporal correlations in wind data on neural network-based wind predictions is accepted in Energy [arXiv link]!
Congratulations to Heesoo for this achievement!
(2023-05) VISIT NEWS
Sangseung and Heesoo visit Nordita (Stockholm, Sweden) to co-organize "FLOW for Climate: Data-driven methods" and present "AI-Assisted Fluid Engineering for Sustainable Future"
(2023-04) IMPACT NEWS
Sangseung's paper "Data-driven prediction of unsteady flow over a circular cylinder using deep learning" published on Journal of Fluid Mechanics (2019) [link] reached 200 citations!
(2022-11) NEW PAPER ALERT!
Heesoo's review paper "Neural Networks for Improving Wind Power Efficiency: A Review" is published on Fluids [link]!
(2022-02) NEW PAPER ALERT!
Sangseung's paper "Predicting drag on rough surfaces by transfer learning of empricial correlations" is published on Journal of Fluid Mechanics [link]!