I have teaching experience as an instructor in undergraduate classes, teaching assistant at both undergraduate and graduate level, and as a workshop instructor.
This is a two-day introduction to causal inference using both Potential Outcomes and Directed Acyclic Graphs. I have offered this workshop several times, including in our local SICSS-UCLA site.
This was a guest lecture on Stat 256 at UCLA, a graduate causal inference class taught by Chad Hazlett. I provided a quick introduction to the estimation of heterogeneous treatment effects, including machine learning approaches. [Slides]
Formation and development of Modern Society (Sociology, PUC Chile, Fall 2017)
Quantitative Methodology (Government, Universidad de Talca, Chile, Fall 2017) [Apuntes de clase]
Causality (Statistics, graduate), Introduction to Sociology, Introduction to Sociological Research Methods, Statistical and Computational Methods for Social Research (Sociology, undergraduate)
Causal inference (Sociology, graduate), Critical Theory: Frankfurt School, Philosophical Anthropology (Philosophy, undergraduate), Historiography, Contemporary History, and 20th Century Latin America (History, undergraduate)