معرفی
Sam Silva is Assistant Professor in Earth Sciences, Civil and Environmental Engineering, and Population and Public Health Sciences at the University of Southern California. He leads the Atmospheric Composition and Earth Data Science group, investigating atmospheric chemistry's role in air quality and climate change through computational modeling and machine learning.
Silva holds a PhD in Environmental Engineering and Computation from MIT and a BSc in Physics and MSc in Atmospheric Science from the University of Arizona. Previously, he was a Linus Pauling Distinguished Postdoctoral Fellow and Research Data Scientist at Pacific Northwest National Laboratory.
Research focuses on atmospheric chemical composition using computer models, data science, and machine learning to address global environmental challenges. Work emphasizes aerosol-cloud interactions, chemical cycling dynamics, climate-health relationships, and equitable modeling approaches.
Publications demonstrate strong trends in developing machine learning frameworks for atmospheric and climate science, with applications in chemical transport modeling, health impact assessments, and biogeochemical cycling. Recent work advances interpretable AI methods while addressing urban air quality-climate interactions.
