I’m trying to free your mind, Neo.
But I can only show you the door.
You’re the one that has to walk through it.
I love teaching, and realize that where I am today is due to some of the amazing teachers I've had along the way; so I try to give back as best as I can.
At Williams College
Fall 2022: Machine Learning
Spring 2022: Causal Inference and Introduction to Computer Science
Fall 2021: Causal Inference
At Johns Hopkins University
Spring 2021: Machine Learning: Data to Models which focuses on the theory and applications of probabilistic graphical models. Here's the syllabus and reviews.
Intersession 2020: Co-created and co-instructed an introductory causal inference course titled "Should Susan Smoke: An Introduction To Causal Inference" with Razieh Nabi. Here's the syllabus. The course was featured in the Hopkins Hub magazine.
Spring 2018: Guest lecture. An introductory tutorial on machine (mostly deep) learning for computational genomics in the Foundations of Computational Biology course taught by Rachel Karchin.
Fall 2017: Co-instructed Intermediate Programming with Sara More. Here's the syllabus and reviews.