As part of the Extreme Wind Resilience Center (EWRC), I work closely with the Wind Engineering Research Laboratory and the Department of Atmospheric Sciences. My current work is using machine learning to identify storm mode for extreme wind events. Using this data, I will create an extreme wind climatology for the United States which can be used in the processes of designing resilient buildings. Currently buildings are designed to withstand wind speeds that are based on synoptic and non-synoptic wind events. It has been shown that each storm mode has differing small scale characteristics which impact the wind loading on structures differently. In addition to building the framework needed to design buildings to withstand a variety of storm modes.

Another part of my research is conducting field work. The focus of this field work is obtaining high resolution surface wind data (temporally and spatially) to understand the small-scale characteristics of surface-based winds. Within the Wind Engineering Research Laboratory, we have pressure sensors that are quickly deployed to utility poles along with other instrumentation such as wind towers. We deploy our fleet of instrumentation both locally and as part of field campaigns such as PERiLS. In both locations, we have coordinated our deployment with the DOWs as a way to obtain additional information on the storm and wind characteristics. Another aspect of my research is wind speed estimation which involves post event damage surveys. I have conducted surveys for the 2021 Western Kentucky Tornado, the 2022 New Orleans Tornado, and the PERiLS Campaign tornadoes.