Current teaching

Fall 2016:
Honors I: Introduction to Stochastic Processes
Monday/Wednesday 3:30pm-4:45pm

Description: This course will be an introduction to stochastic processes. Topics to be discussed include Markov chains, Poisson process, Brownian motion, a little bit of Ito calculus, and some simulation methods like Markov Chain Monte Carlo. It will be a mixture of theory and applications, and will be as rigorous as it can without getting into measure-theoretic arguments.

The prerequisites are calculus, linear algebra, and probability theory. Although these are the only technical mathematical prerequisites, the course will assume a level of mathematical sophistication that goes beyond simply these raw courses; e.g. you should be comfortable with proofs, and with the higher-level mathematical arguments found in courses like analysis.

A little bit of programming will be required, but you do not have to have experience with this beforehand as we will cover the necessary elements in class. We will probably use Python for examples in class, but you could also use Matlab or R if you are more familiar with these.

Textbook: Introduction to Stochastic Processes, by Robert Dobrow.
Available for purchase from the publisher or from amazon or the NYU bookstore.


Teaching materials



cSplash

In 2006 I co-founded cSPLASH , a one-day festival of mathematical sciences for high school students, taught by undergraduates, graduate students, and professors from New York University and nearby. It is now held once a year in the spring. You can get involved by participating as a high-school student, teaching a class on math, science, or computer science, organizing it in advance or volunteering on the day of the event. To find out more, visit the website below.

Past Teaching

To be updated.