Teaching

I teach Data Literacy for Psychology (PSYCH-UA 8) in the Fall and Machine Learning for Climate Change (DS-UA 301) in the Spring.

Course Materials

Machine Learning for Climate Change (Spring 2024)

The course has been redesigned to focus more on research papers. Materials will be posted as the course progresses.

Syllabus

Lecture 1 - Intro + Climate Change + Building Energy Use + Regression

Lecture 2 - Paper 1 + Extreme Weather/Disaster + Comp Vision + ANNs

Lecture 3 - Paper 2 + Ocean Impacts + CNNs + Segmentation

Lecture 4 - Paper 3 + Climate Models + GANs and Self-Supervision

Lecture 5 - Paper 4 + Agriculture + Time Series + Transfer Learning

Lecture 6 - Paper 5 + Human Psychology + NLP + Transformer

Lecture 7 - Paper 6 + Careers + Projects + Exam Prep

Lecture 8 - Climate Finance + Recommender Systems + Genetic Algorithms

Lecture 9 - Paper 7 + Transportation + Reinforcement Learning

Lecture 10 - Paper 8 + Power Grid + Graph Neural Networks

Lecture 11 - Paper 9 + Carbon Dioxide Removal + Review + Multi-task Learning

Lecture 12 - Paper 10 + Exam 2 Prep

Machine Learning for Climate Change (Spring 2023)

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