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Francesca Dominici: Decoding Climate Vulnerability

Lecture is sold out - view recording after event

Event Details:

Tuesday, February 28, 2023
6:30pm - 9:00pm PST


Stanford University
Mackenzie Room, Huang Engineering Center
475 Via Ortega
Stanford, CA 94305-4121
United States

This event is open to:

General Public

Logistics for in-person talk

We are pleased to announce the first Stanford Data Science Distinguished Lecture this February 28th, at 7:30pm. We welcome you to join us at 6:30pm for a cocktail reception and an opportunity to engage with others in the Stanford Data Science community and beyond. 

Our speaker is Dr. Francesca Dominici, who will speak on Decoding Climate Vulnerability: Harnessing the Power of Data Science and Causal Inference.

Dr. Francesca Dominici is Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and Co-Director of the Data Science Initiative at Harvard University. She was recruited to the Harvard Chan School as a tenured Professor of Biostatistics in 2009. She was appointed Associate Dean of Information Technology in 2011 and Senior Associate Dean for Research in 2013.


Air pollution and climate change are two sides of the same coin. Pollutants emitted in the air can lead to changes in climatic conditions. These emissions consist of greenhouse gases. Specific components of particulate matter can either warm or cool the temperature. Short-lived climate pollutants are also dangerous air pollutants that harm people, ecosystems, and agricultural productivity. On January 6, 2023, the Environmental Protection Agency (EPA) announced a proposal to lower the National Ambient Air Quality Standard (NAAQS) for annual PM2.5 pollution from 12 μg/m3 to between 9 and 10 μg/m3, though it continues to consider other options. Data science must inform this decision.

In this talk, I will provide an overview of data science methods, including methods for causal inference and machine learning, with the lens of policy change. This is based on a large effort of analyzing a data platform of unprecedented size and representativeness. The platform includes more than 600 million observations on the health experience of over 95% of the US population over 65 years old linked to air pollution exposure and several confounders. I will also provide an overview of studies on air pollution exposure, environmental racism, wildfires, and how they can exacerbate vulnerability to COVID-19.
Swift action on reducing short-lived climate forcers such as methane, tropospheric ozone, hydrofluorocarbons, and black carbon can significantly decrease the chances of triggering severe climate tipping points.

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