Quan Wei now is a Ph.D. student at the University of Minnesota, Minneapolis, MN, USA. Previously, he received his master degree from ShanghaiTech University, China.

At the DSAI lab, Quan has primarily focused his research on two key areas: high-dimensional sparse covariance matrix estimation and high-dimensional sparse regression.

high-dimensional sparse covariance matrix estimation

• Large Covariance Matrix Estimation With Oracle Statistical Rate via Majorization-Minimization Quan Wei, Ziping Zhao
  IEEE Transactions on Signal Processing, 2023
  Short version:
  Large Covariance Matrix Estimation With Oracle Statistical Rate [Best Student Paper Award]
  Quan Wei, Ziping Zhao
  IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
  
  
• Large Covariance Matrix Estimation for Heavy-tailed Distributions via Regularized Huber’s M-Estimator Jialin Yu, Quan Wei, Ziping Zhao

high-dimensional sparse regression

• Adaptive Selection of Sparse Reduced-Rank Regression
  Quan Wei, Ziping Zhao
  Short version:
  Sparse Reduced-Rank Regression With Adaptive Selection of Groups of Predictors Quan Wei, Yujia Zhang, Ziping Zhao
  Asilomar Conference on Signals, Systems, and Computers, 2021
  
  
• High-Dimensional Robust Regression in Networks
  Quan Wei, Ziping Zhao
  Short version:
  High-Dimensional Constrained Huber Regression [Best Student Paper Award Finalist]
  Quan Wei, Ziping Zhao
  IEEE Sensor Array and Multichannel Signal Processing (SAM) Workshop, 2024