Geophysical Field

Geophysical field research focuses on reconstructing and predicting complex, often partially observed, physical systems like ocean currents and temperature distributions using diverse data sources. Current research emphasizes the development and application of advanced machine learning techniques, including convolutional neural networks, autoencoders, and neural ordinary differential equations, to improve the accuracy and efficiency of inversion methods and forecasting models. These advancements are crucial for enhancing our understanding of geophysical processes and improving applications such as optimal sensor placement, data assimilation from multiple satellite sources, and more accurate predictions of environmental phenomena.