DES Seminar:
Tired of Sparse Environmental Data and Slow Simulations? Here is a Coastal Flooding Example Showing Data Science Can Help

Abstract: 

In the big data era, it is still difficult to rely on the model-based design to mitigate natural hazards, optimize infrastructure planning, and address urban environmental problems. On the one hand, we lack tools to mine and fuse the growing big data to improve the numerical model. On the other hand, we have difficulties to use the high-fidelity models to support decision-making. As data science and data-driven algorithms emerge, there is an opportunity to apply and develop a suite of new methods to connect data, especially the unconventional big data, and high-fidelity models to address the model-based decision-making issues of urban and coastal resilience. My talk will focus on my existing studies of big-data monitoring of urban floods and data-driven analysis for coastal infrastructure optimization.