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Bayesian Data Assimilative Ocean Forecasting, Learning, and Optimal Sensing for Sustainable Fisheries Management in India

This project will develop Bayesian data-driven estimation and model learning methods, stochastic forecasts, and analysis products for ocean physics, biogeochemistry and fisheries. Our data-assimilative ocean field and uncertainty estimates, optimal data collection guidance, and coastal ecosystem-based scenario and risk analyses will serve as quantitative technical decision aides for sustainable rights-based fisheries management. Our forecasts have diverse local commercial and societal applications involving not only fisheries but also coastal zone management, pollution mitigation, monitoring, ocean engineering, tourism, shipping, financial hedging, and re-insurance. In addition to educating students, we also collaborate with colleagues from IISc Bangalore (Prof. Deepak N. Subramani), governmental and non-governmental agencies to transfer our technology and train the users.