Teaching

Statistical Learning (i.e. Machine Learning)

I taught statistical learning for PhD students in psychology with Patrick Mair. I received additional grant funding from Harvard to design and create sections for this course. Each section involved programming in R and a discussion of conceptual material (sometimes a review, sometimes new material). I received the Bok Center for Teaching and Learning teaching award for teaching sections of this course. I also received perfect teacher evaluations (average 5.0/5.0, from 23 total student reviews).

We taught the following topics:

• Clustering

• Markov Chain Models

• Principles of Supervised Learning

• Regularization (e.g. LASSO)

• Tree-based approaches, including Random Forests and Boosted Trees

• Support Vector Machines

• Basics of Natural Language Processing

• Basics of Neural Networks

Cognitive Neuroscience

I taught introduction to cognitive neuroscience for undergraduates with Dan Schacter, George Alvarez, and Liz Phelps. I received the Bok Center for Teaching and Learning teaching award for teaching sections of this course.

We covered the following topics:

• Basics of Cognitive Neuroscience Methods

• Perception

• Attention

• Memory

• Language

• Emotion

• Social Cognition

Introduction to Statistics for the Behavioral Sciences

I taught an applied introduction to statistics class with Patrick Mair and Thomas Rusch. I served as the head teaching fellow, supervising several other teaching fellows. I received the Bok Center for Teaching and Learning teaching award for teaching sections for this course.

I covered the following topics in R:

• Descriptive Statistics

• Data Visualization

• Correlation

• Regression

• ANOVAs

• Power & effect sizes