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3203 Southeast Woodstock Boulevard, Portland, Oregon 97202-8199

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Sam Silva is currently a Linus Pauling Distinguished Postdoctoral Fellow at Pacific Northwest National Laboratory. He received a Ph.D. in Environmental Engineering and Computation from the Massachusetts Institute of Technology, and an M.S. in Atmospheric Science and B.S. in Physics from the University of Arizona. His research largely focuses on the chemical composition of the atmosphere, with particular interest in biosphere-atmosphere interactions, application of remote sensing observations, and development and implementation of data science and A.I. methods in the Earth System Sciences.

Data Science, A.I., and Atmospheric Chemistry

Understanding the controlling factors behind the chemical composition of the Earth’s atmosphere is a critical step toward addressing the modern environmental challenges of air pollution and climate change. Traditional methods interrogating theoretical predictions with observations have been highly successful in addressing these challenges, particularly in light of the recent immense growth of data availability in the Earth System Sciences. However, there are still gaps in our scientific knowledge due to limitations in modern scientific techniques (e.g. theoretical frameworks, observational systems, and computational power). New methods from the data science and artificial intelligence (A.I.) literature, when informed and guided by scientific understanding, present a valuable tool in addressing these knowledge gaps. 

In this seminar, I will present results from recent work using a variety of data science and A.I. methods to better constrain modern understanding of atmospheric composition. Specifically, we applied a set of tools known as Deep Neural Networks to develop an improved model for the interactions between ozone (O3) and the plant biosphere, and we are currently working on using graph theoretic models to better understand and compare various representations of gas phase atmospheric chemical reaction networks.

This event is supported by the Thomas Dunne Lecture Fund.

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