About Shuo-Chieh

Hello! I am a postdoctoral researcher in the Department of Statistics at Rutgers University. 

My research studies manifold-valued data and machine learning algorithms from a dynamic viewpoint. Specifically,

• I study how algorithms statistically learn from data through each iteration—providing rigorous statistical convergence analysis and designing efficient learning algorithms;

• I develop methods for analyzing manifold-valued time series—examining temporal dependence beyond linear autocorrelations—by integrating tools from statistics and geometry. 

In addition to theoretical contributions, I work mainly with economic, financial, and environmental data to provide actionable insights.

Prior to Rutgers, I received my Ph.D. in Econometrics and Statistics from the Booth School of Business, University of Chicago. 

• Manifold-valued data

• Time series and complex dynamics

• Optimization and computing

• Econometrics

[Google scholar]