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Tired Of Sparse Environmental Data And Slow Simulations? Here Is Coastal Flooding Example Showing Data Science Can Help

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Friday, 11 October 2019, 2:30

Friday, October 11, 2019.  2:30 PM. Tired Of Sparse Environmental Data And Slow Simulations?  Here Is Coastal Flooding Example Showing Data Science Can Help. Dr. Ruo-Qian (Roger) Wang, Rutgers University. Sponsored by Dept. Of Environmental Sciences. More information.


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.



Dr. Roger (Ruo-Qian) Wang is an Assistant Professor at the Department of Civil and Environmental Engineering, Rutgers University since 2019. He was a Lecturer of Fluid Mechanics in Civil Engineering at the University of Dundee from 2017-2018. He has conducted Postdoctoral research in Civil and Environmental Engineering at the University of California, Berkeley, and Mechanical Engineering and Tata Center for Research and Technology at MIT. He has obtained a PhD in Environmental Fluid Mechanics at MIT, a Master's degree from Singapore-Stanford Partnership (Nanyang Technological University /Stanford University), and a Bachelor's degree from Beihang University, China. He has also served as a research engineer in Singapore-MIT Alliance for Research and Technology Center before his Ph.D.


Location  Room 223, Environmental & Natural Resource Sciences Bldg, 14 College Farm Road, New Brunswick, NJ