Joongoo-Jeon Jeon

Professor Joongoo-Jeon Jeon's research lab specializes in computational fluid dynamics and machine learning for turbulent flow prediction, focusing on data-driven modeling of complex, high-dimensional fluid systems. The lab explores generative deep learning models—particularly diffusion models—to improve the accuracy and physical consistency of long-term predictions in two- and three-dimensional turbulence. Key research directions include the development of physics-informed neural networks, uncertainty quantification in turbulent flow forecasting, and the preservation of fine-scale structures and energy spectra in predictive models. The lab also investigates time-interval effects and error accumulation in autoregressive prediction frameworks, aiming to bridge the gap between machine learning generalization and physical fidelity in fluid dynamics.