Teaching
I usually teach Data Literacy for Psychology (PSYCH-UA 8) in the Fall and Machine Learning for Climate Change (DS-UA 205) in the Spring. In Spring 2025, I also taught (with Marcelo Mattar) a graduate course on neural network models of the mind and brain.
For videos covering academic papers that apply AI to climate change and ecology, check out my YouTube channel 5 minute papers on AI for the Planet
Course Materials
Machine Learning for Climate Change (Spring 2026)
In this course, students read academic papers applying machine learning to climate change problems and engage in course discussions on them. Lectures prepare students for these readings by introducing aspects of mitigation and adaptation to climate change as well as covering machine learning topics. Any instructors interested in using materials for their own course, please contact Grace directly to access all lectures and readings.
Machine Learning for Climate Change (Spring 2023 - old class format)
Syllabus. Course Overview/Introduction to Climate Science | The Problem of Climate Change | Energy Efficiency - Buildings and Cities | Energy Efficiency - Supply and Demand | Tracking GHG Emissions - Estimation Methods | Tracking GHG Emissions - Transportation | Food and Agriculture - Problems and Opportunities in Agriculture | Food and Agriculture - Food Packaging and Waste | Alternative Energy - Renewables | Carbon Dioxide Removal - Biological and Chemical | Midterm Review | Project Instructions | Influencing People/Climate Communication | Climate Finance | Career Day | Disaster Response | Health Impacts | Extreme Weather Prediction | Predicting Food Shortages | Automated Farming | Climate Migration