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  • Uncertainty Quantification

    Uncertainty Quantification and Data Assimilation Research

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  • Path Planning

    Path Planning of Autonomous Underwater Vehicles

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  • ML and AI

    Machine Learning and Artificial Intelligence for Geoscience Research

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Uncertainty Quantification and Data Assimilation

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Path Planning

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Stochastic Ocean Modeling

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Machine Learning and Artificial Intelligence

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About Us

The goal of our research is to build holistic science-based data-driven computational solutions to complex engineering and environmental problems. Example applications include climate change, sustainable fisheries management, cyclone predictions, coastal hazard management, and optimal vehicle routing. Pursuant to our goal, we develop, implement and apply fundamental theories, numerical schemes and software systems.

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Physics-Driven Machine Learning for Time-Optimal Path Planning in Stochastic Dynamic Flows

Chowdhury, R and Subramani, D.N.