Teaching

CS 159: Advanced Topics in Machine Learning

I am co-teaching the spring 2021 incarnation of CS 159 with Yisong Yue and Ugo Rosolia. The class involves 12 lectures on advanced material in machine learning, after which the students spend a month working on a final project.

My portion of the class involves 6 lectures on neural network theory, covering various aspects including neural architecture design, optimisation, network function spaces and PAC-Bayesian generalisation theory.

3-Minute Video Workshop

In fall 2019, I organised a videomaking workshop with Tatyana Dobreva and David Brown. The idea was to teach students to effectively present their work to a wider audience through a modern medium.

We contracted professional science Youtubers to teach videomaking, and a professional filmmaker to shoot the students' final projects. You can watch the end results on Caltech Neuroscience's Youtube page. If you'd like to replicate our workshop at your own institution, read our report here.

Oh, and here's how my video turned out:

Teaching Assistantships

CMS 117: Probability Theory & Stochastic Processes · Fall 2019 · Tropp
CS 159: Advanced Topics in Machine Learning · Spring 2019 · Yue