August Posch is a data scientist in the AI for Climate and Sustainability (AI4CaS) focus area at the Institute for Experiential AI. His projects include phenology-guided AI techniques for remote sensing-based land cover classification, climate downscaling for precipitation extremes and associated impacts on urban rail infrastructures, and precipitation nowcasting with hydrologic evaluation for dam management.

After earning a bachelor’s degree in mathematics from Bowdoin College, August created data pipelines and reports for L.L.Bean’s marketing team. He earned a master’s degree in data science from the Roux Institute and Khoury College at Northeastern University, focusing on geospatial applications, such as gentrification mapping, wildfire prediction, and urban rail ridership prediction. He began working with Dr. Auroop Ganguly at SDS Lab at Northeastern, creating a phenology-guided AI system for remote sensing-based land cover classification, funded by a U.S. Army Corps of Engineers grant. August is excited about new ways to use machine learning to solve humanity’s problems.