In the academic year 2025-26 I will be teaching Data Analytics and Time Series Analysis (F71DA, for Masters students). Details and course materials can be found on Canvas.
I have regularly taught parts of the core SMSTC modules Foundations of Probability (Semester 1) and Stochastic Processes (Semester 2) for PhD students. Further details of these modules can be found on the SMSTC website.
Notes from a one-off lecture I gave in December 2013 (on "The central limit theorem and Poisson approximation: An introduction to Stein's method") as part of the SMSTC Probability stream can be found here (now with some minor typos corrected).
In August 2022 I gave a mini-course on "Probability approximations using Stein's method: Random graphs, Markov chains and beyond" at the LMS Undergraduate Summer School 2022. Materials from this mini-course are available below.
Please click here for lecture notes.
Tutorial 1 and solutions
Tutorial 2 and solutions
The folllowing resources are not used directly in the course, but may be useful as a starting point for anyone who wants to do some further reading:
Fundamentals of Stein's Method: 2011 survey paper by Nathan Ross
Stein's (Magic) Method: 2014 survey paper by Andrew Barbour and Louis Chen
A Short Survey of Stein's Method: 2014 survey paper by Sourav Chatterjee
Notes from an introductory lecture on Stein's method for graduate students I gave in 2013
Website cataloging developments in Stein's method, maintained by Yvik Swan
Website cataloging developments in the Malliavin-Stein method, maintained by Ivan Nourdin