Selected Research Projects

Click to see the relevent papers.


We develop classification methods as well as their corresponding theory under various contexts.


We study various statistical aspects of network type data including modeling, estimation and algorithms.

Nonparametric statistics

We study nonparametric estimation methods with applications.

Tuning parameter selection

We investigate the tuning parameter selection problem under various contexts.

Variable selection

We propose different methods for performing variable selection in various contexts.

Selected Publications

Click on the ‘Project’ button under each paper to view other related papers.

Complete Publication List

(2017). How Many Communities Are There?. Journal of Computational and Graphical Statistics.

PDF Code Project Journal Link

(2016). Neyman-Pearson Classification under High-Dimensional Settings. Journal of Machine Learning Research.

PDF Project Journal Link

Recent Posts

Random thoughts and notes

Mac has native python installed with version 2.7. However, we sometimes want to use python 3. The following are easy steps to run python 3 along the system default version 2.7.

Step 1: Install brew if not yet done.

/usr/bin/ruby -e "$(curl -fsSL"

Step 2: Install pyenv and python 3.6.0.

brew install pyenv
pyenv install 3.6.0
virtualenv -p /Users/yangfeng/.pyenv/versions/3.6.0/bin/python3.6 myenv
. ./myenv/bin/activate && python -V


Finally finished converting my website using the hugo academic theme!



I have been teaching the following courses at Columbia University.

  • GR6102: Statistical Modeling and Data Analysis (II)
  • GR6101: Statistical Modeling and Data Analysis (I)
  • W2024: Applied Linear Regression Analysis
  • W4315: Linear Regression Models
  • G8325: Advanced Topics in Statistics (Statistical Analysis for Network Data)
  • G8325: Advanced Topics in Statistics (High-dimensional Variable Selection)
  • W1211: Introduction to Statistics (with calculus)