Climate Change Health AI
Irene Chen, Professor
Computational Precision Health
Closed. This professor is continuing with Fall 2023 apprentices on this project; no new apprentices needed for Spring 2024.
This project involves leveraging AI techniques to model and predict health outcomes resulting from extreme weather events due to climate change.
Role: The undergraduate student will curate diverse spatiotemporal datasets linking granular climate information to patient health information. Initial experiments will train prediction models to forecast climate-attributable disease burdens and mortality at a patient-level across the U.S. Additional work may leverage graph neural networks, audit models for health disparities, and investigate the impact of health interventions. This project combines climate science and health data to advance AI capabilities for the societal challenge of climate change preparedness and response.
Prof. Chen is an Assistant Professor in Computational Precision Health and Electrical Engineering and Computer Science. Her research group values curiosity, collaboration, compassion, and inclusion. We uphold rigorous standards of quality research and ethics, while ensuring each person is regarded first as a human with goals that are understood and supported. Our culture enables scholars to produce their best work.
Qualifications: Ideal candidates will be undergraduate students with coursework or experience in areas like machine learning, data science, and climate science. The ability to code in Python is preferred. Students are expected to meet with the faculty mentor twice a week, and will be trained to conduct literature review, formulate research problems, and engage in scientific writing.
Hours: 12 or more hours
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