Spatiotemporal Ocean Data Analytics

Ocean research is undergoing a data revolution with new data streams coming online and constantly increasing in volume. Emerging research in data analytical methods needs to be tailored to the specific challenges of ocean data, including heterogeneous data types, spatial and temporal dependencies, and high-volume streaming data. The proposed research aims to develop novel spatiotemporal learning algorithms to obtain models useful in areas such as biodiversity analysis, ocean / atmospheric interactions, and ship tracking. Collaborations with domain experts and end users in industry and government will maximize the impact of the research, and create new opportunities for multidisciplinary training.