Teaching

IIES, Stockholm University

Macroeconomics II (PhD)

Spring 2024, Instructor

First-year PhD course. Business cycles, asset pricing, search theory, New Keynesian models, incomplete markets models.

University of Pennsylvania

I am the recipient of the 2020 Joel Popkin Graduate Student Teaching Prize in Economics

The Digital Economy

Spring 2023, Teaching Assistant

Professor Juan Camilo Castillo

Undergraduate advanced level course. Features of digital markets, including network effects, two-sided markets, search and matching, reputation systems, and the use of data. Zoom in on individual markets: search engines, e-commerce platforms, and the gig economy. Understanding how digital markets should be designed and regulated.

Intermediate Macroeconomics

Spring 2022, Teaching Assistant

Professor Guillermo Ordonez

Undergraduate intermediate level course. Facts and theories about the determination of per capita income and its differences across countries and across time. The study of economic fluctuations. The role of government in influencing these aggregate variables: monetary and fiscal policy.

Macroeconomic Theory I (PhD)

Fall 2019, Spring 2019, Teaching Assistant

Professors Dirk Krueger and Jesus Fernandez-Villaverde

First-year PhD course. Dynamic programming, search theory, neoclassical growth theory, asset pricing, business cycles.

Data Science Initiative

Summer 2020, Organizer and co-Instructor

Professor Bhuvnesh Jain

Undergraduate level summer initiative for students in the humanities, social sciences and natural sciences. Basics of programming in Python, probability and statistics, datasets, analysis, data visualization, introduction to machine learning and neural networks.

Python for Data Science

Summer 2019, Organizer and co-Instructor

Professor Bhuvnesh Jain

Graduate level summer initiative for students in the humanities, social sciences and natural sciences. Programming in Python, reading and visualizing data, text data and scraping, inference, machine learning, neural networks and deep learning in Python.