Rose Yu

In this engaging discussion, Rose Yu, an assistant professor at UC San Diego, delves into her groundbreaking work on machine learning for spatiotemporal data. She explains how integrating physical principles and symmetry enhances neural network architectures. The conversation covers innovative approaches in climate modeling, including turbulent prediction and the application of Physics Guided AI. Rose also addresses uncertainty quantification in models, crucial for applications like COVID-19 forecasting, showcasing the importance of confidence in predictions.