Jack Hayes is an MS student interested in using active remote sensing and machine learning to monitor and forecast natural hazards. His current work supports NASA’s STV mission and incorporates the identification of data fusion sites in order to produce higher resolution DEMs. See the ‘coincident’ pachage at https://coincident.readthedocs.io/en/latest/ for more information.

Jack was born and raised in Arlington Virginia, ending up at William & Mary for undergrad where he recently graduated in 2024. Jack was involved in a wide breadth of research at W&M, conducting qualitative conservation fieldwork in Nepal, developing machine learning algorithms to detect continuous gravitational waves, and supporting spatial analysis that quantified racial gerrymandering in the US. He also spent a lot of his time playing ultimate frisbee and contributing to a mobile app that made it easier for tourists to explore Williamsburg, VA. He worked as an NSF REU Fellow and Data Scientist at Harvard’s Center for Geographic Analysis and an Intern at the Harvard College Observatory before joining UW.

When he isn’t conducting research, Jack enjoys spending time outdoors, playing piano and classical guitar (hopefully jazz as well soon), and lifting weights. He’s more than happy to talk with anyone about grad school, maps, driving across the country to move to Seattle, and much more!