Teaching

Goldman School of Public Policy

In Fall 2023, I am teaching Statistics for Program Evaluation (PP 249).

Previously, I have taught:

• Statistics for Program Evaluation (PP 249; Fall 2016, 2017, 2019-2021)
• Data Science for Public Policy (PP 290; Fall 2016; Spring 2020, Fall 2020, Spring 2022)
• Core Data Analysis & Visualization Skills Workshop (PP 297; Fall 2016, 2017)
• Analytics for Government and Policy (PP 290; Spring 2016)

Department of Statistics

Previously, I co-organized the Berkeley causal inference research group with Peng Ding, Erin Hartman, Sam Pimentel, Vira Semenova, and Jingshen Wang.

From 2016 to 2019, this meeting was organized as a reading group. Previous topics included:

• Causal inference and time (Fall 2019)
• Semiparametric approaches to causal inference (Spring 2019)
• Applying causal inference to the social and behavioral sciences (Fall 2018)
• Foundations of causal inference (Spring 2018)
• Optimal study design in causal inference (Fall 2017)
• Causal inference with interference (Spring 2017)
• Causal inference in high dimensions (Fall 2016)