Mentor(s)

Christopher Horvat, Earth, Environmental & Planetary Sciences, Brown University, Michelle McCrystall, Physics, University of Auckland

Project Location

Brown University

Project Description

EMPIRIC is a multi-institutional collaboration to provide better hurricane impact metrics in a warming world. We are working to develop a machine-learning-aided model for cyclone impacts in the Atlantic and Pacific and using it to understand future impacts of cyclones on coastal environments. We are hoping that we can use these models to understand climate-driven impacts on human health, particularly on health facilities in the crosshairs of potentially stronger cyclones.

The student(s) will be tasked with one of a few potential objectives under the EMPIRIC umbrella:

1) Helping to develop a neural-network architecture for tropical cyclone impacts in coastal communities.
2) Participating in knowledge transfer about impacts of cyclones on health for communities in the Pacific.
3) Building and analyzing cyclone risk projections using new-generation AI forecast models.
4) Analyze the response of the upper ocean phytoplankton to passing storms with remote sensing.

The student will work with our broad collaborative team and participate in bi-weekly meetings, and help with the preparation of presentations and datasets for dissemination to partners at the WHO, SPC, and partner countries.

This project involves computational work

Required/Preferred skills

Familiarity with programming/data science concepts, and ability to write and understand code in Python/Matlab. Some background in machine learning/AI would be helpful. Most importantly, an interest in climate and in communicating climate science concepts!

Will the project require transportation to field sites? No

Is this project open to Surf Flex? Yes

In which core facilities might student conduct research? Brown’s Center for Computation and Visualization

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