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Lab Member Drive Received Stanford Centennial Teaching Assistant Award

The award recognizes Drive's talent at "breaking down complex topics to be digestible and for tailoring his tutoring rigor to the level of each individual"

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  • This work introduces a ML-based source apportionment model that leverages multiscale aerosol composition data to achieve near-real-time tracking and accurate quantification of PM2.5 sources. The findings support near-real-time source analysis and integration into policy.