Teaching

🏫 @ Beijing Normal University

• Statistical Computing · Spring 2026:
  • Full Lecture Videos on Bilibili 📺 (in progress);
  • Lec 1. Solving Nonlinear Equations;
  • Lec 2. EM;
    • Lec 2.1. EM Cases;
    • Lec 2.2. Hidden Markov Model;
  • Lec 3. Monte Carlo;
  • Lec 4. MCMC;
    • Lec 4.1. Advanced MCMC;
    • Lec 4.2. Hamiltonian Monte Carlo;
    • Lec 4.3. Markov Random Field;
  • Lec 5. Variational Inference and Pyro;
    • Lec 5.1. Variational Autoencoder;
    • Lec 5.2. Diffusion Models;
  • Lec 6. Bootstrap and Permutation Test;
  • Extra: Algorithmic Problems

🏫 @ The Chinese University of Hong Kong

• STAT2005 Programming Languages for Statistics:
  • Tut 1. Introduction to R;
  • Tut 2. Random Numbers;
  • Tut 3. Statistical Graphics;
  • Tut 4. Attributes;
  • Tut 5. Debugging, Outer and Objects;
  • Tut 6. Matrix, R packages;
  • Tut 7. SAS, ggplot2;
  • Tut 8. SAS data set;
  • Tut 9. Data Manipulation;
  • Tut 10. Controlling Output Contents

• STAT2006 Basic Concepts in Statistics and Probability II: link

• Fundamentals of Deep Learning Workshop: link

• Fundamentals of Accelerated Data Science: link