Megan Ayers
Assistant Professor of Statistics
Mathematics and Statistics Department
Division of Mathematical and Natural Sciences
Megan Ayers is a statistician and data scientist whose interests include causal inference, experimental design, machine learning, and social and environmental applications of statistics. Her recent research focuses on statistical methodology for deforestation policy evaluation and forest carbon markets, as well as developing machine learning methods for causal inference with text data. Her applied work has also included research on climate change communication and public opinion. She is passionate about teaching statistics at all levels and particularly enjoys courses that integrate R, real-world data, and project-based learning. Megan earned her B.A. in Mathematics and B.A. in Physics from Lewis & Clark College, and her PhD in Statistics & Data Science from Yale University.