Working on the development of sparse statistical modelling techniques.

Xinle completed his undergraduate degree in Mathematics at the University of British Columbia and his Master’s degree at the George Washington University in Statistics.

Research project title:
Development of Sparse Statistical Modelling for Neurological Applications

Supervisor(s): 

Sandipan Roy, Matthew Nunes

Project description:
This project aims to develop an alternative method using techniques such as low-rank approximation or sparsity, which do not impose restrictive model assumptions. The approach will be supported by an associated estimation theory and a fitting process based on constrained optimization to ensure robust and efficient estimation.