Third-year course teaching principles of regression, hypothesis testing, elements of causal inference

Using R as statistical software and matrix algebra.

Helped roll out unified Stata coding and data analysis platform on GitHub across undergraduate cohorts 

Designed and coded automated grading in R for empirical data submissions in applied macro

Guest lecturer and suggestions for readings for causal machine learning master's course

Advised MA Economics students in the doctoral stream on research paper topics in theoretical and applied econometrics

Held weekly meetings to discuss progress, gave feedback on research direction, proposals, presentations

Econometric Theory I and II (PhD)

Causal Machine Learning (MA)

Causal Inference, Applied Econometrics (Advanced Undergraduate)

Data Analysis & Applied Econometrics in Practice, Intro to Data Analytics & Big Data, Topics in Data Analytics, Money & Banking, Intro to Microeconomics, Intro to Macroeconomics (Undergraduate)