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Gabriel Presented in Stanford Undergraduate Research Symposium

Gabriel Tsai presented his recent research on machine learning of warm rain microphysics during the Stanford Undergraduate Research Symposium

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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.