Teaching

I am currently scheduled to teach Math 216A in the fall and Math 189 in the winter.

Here are materials from my past courses.

Math 180A: Introduction to Probability

Quarter: Spring

Offered: 2025

This course will teach you to solve problems using the tools of discrete and continuous probability including:

• probability and counting (8 lectures);

• discrete random variables (4 lectures);

• continuous random variables (4 lectures);

• multivariate distributions (6 lectures); and

• the law of large numbers and Central Limit Theorem (3 lectures).

Here are my course materials (hand-written).

Math 216A: Mathematical Methods in Data Science I

Quarter: Fall

Offered: 2024

This course will teach you about fast algorithms for data science. Fast algorithms are needed when there is a large number of data points or the data points themselves are high-dimensional. Mathematical analysis can shed light on the most efficient algorithms, as can numerical experimentation.

Here are my course materials (typed).

Caltech ACM 206: Monte Carlo methods for Scientific Computing

This course introduces Monte Carlo methods with applications in Bayesian computing and rare event sampling. Topics include Markov chain Monte Carlo (MCMC), Gibbs samplers, Langevin samplers, MCMC for infinite-dimensional problems, convergence of MCMC, parallel tempering, forward flux sampling, and sequential Monte Carlo. Emphasis is placed both on rigorous mathematical development and on practical coding experience.

Here are my course materials (hand-written).