Current teaching (2017 Fall)

  • Distributed Statistical Computing for Big Data (graduate level)
  • Bayesian Data Analysis (graduate level)

Past courses

Bayesian Data Analysis

  • 2017 summer, 2017 fall semesters, Central University of Finance and Economics

Statistical Computing

I stared this course when I was helping Mattias Villani for developing the programming course for both undergraduate and master students in Linköping University, Sweden. I also constructed the assignments for the computer lab. Below you can find the course materials. The course was further developed and enhanced by our guest professor Anastasios Panagiotelis from Monash University.

Python for Statisticians

This is an advanced level course for students mastering statistical methods, especially in Big Data analysis. Topics cover basic Python knowledge, data structure in Python, statistical modeling with Python, text mining and natural language process (NLP) and web scraping.

  • Graduate level
  • 2015 fall semester, Central University of Finance and Economics, China

Distributed Statistical Computing in Big Data

A brand new course for Big Data analysis with distributed computing technology.

Statistical Software

The intention of this course to give undergraduate students who already have the knowledge of statistical computing a overview of state-of-the-art statistical computing tools. The course covers the following topics, efficient statistical programming, Statistical programming for big data, and Special topics in Statistical Computing.

  • Undergraduate level
  • 2014 spring semester, Central University of Finance and Economics


The first part of this course focuses on fundamental econometric concepts and models with course book Basic Econometrics by Gujarati and Porter. The second part focuses on time series models with financial applications with course book Introduction to Time Series Analysis and Forecasting by Montgomery, Jennings and Kulahci. This belongs to my 20 percent teaching task for Department of Statistics, Stockholm University during the period 2008 autumn to 2013 spring. Below you can find the course materials.

Time Series Analysis

Topics in time series and financial applications.

Nonparametric regressions

This was the course I taught for master students at Department of Statistics, Stockholm University in 2013 summer. The course includes various topics in nonparametric regressions like splines, shrinkage, kernel regression, surface fitting, cross-validation. The course materials are available in Mondo.

  • Graduate level
  • 2013 spring semester, Stockholm University

 Academic English in Statistics

This course is designed for first year master students. The course is titled as English course but it covers various topics in statistics which includes Bayesian methods, nonparametric smoothing methods, MCMC technology. Besides, it will also touch the ares of scientific writing, presentations. This course is taught in English.

Statistical Case Studies

  • Graduate level
  • 2016 spring, 2017 spring semester, Central University of Finance and Economics