Meaningful experiments and high-quality data
Global challenges associated with extreme climate events and natural hazards require significant advances in our understanding and predictive capability across spatial and temporal scales. Moreover, numerical methods that can address these challenges must be constructed on a mathematically rigorous and computationally robust foundation that itself is built on datasets generated from carefully constructed and well-executed experiments.
New Sensors
One of the major challenges in developing numerical simulations is access to meaningful data. I focus on designing and implementing novel sensing systems, both at the hardware and software levels, that capture key experimental data.
New Testing Techniques
We must always be pushing the boundaries of experimental testing, developing new techniques that allow us to generate high-quality and meaningful data sets while maintaining reasonable cost and time constraints.
New Analysis Tools
Large data sets can be difficult to analyze, especially considering when multiple data acquisition systems are utilized.