Ph.D., The University of Arizona, 2012
B.S., Sichuan University, 2006
Big Data Analysis
Geometry and Statistics: Statistics on Manifolds/ Manifold Learning/ Information Geometry
High-dimensional Data Analysis
Large Sample Theory for Network Analysis
Machine Learning in Neuroscience
Cancer Research Study
Dr. Lin’s theoretical and methodological research focuses on 1) theoretical and methodological foundations for Big data analysis; 2) Bayesian asymptotics for high-dimensional models; 3) geometry and statistics including statistical analysis of complex data such as manifold-valued data; 4) large sample theory for network analysis; 5) computational complexity of MCMC samplers for complex and high-dimensional models.
Dr. Lin’s applied and interdisciplinary research lies in applications in neuroscience with a general goal of developing new machine learning and statistical tools for analyzing large and complex neuroscience data including local field potential data as well as single neuron data. Dr. Lin has also been collaborating with her colleagues on cancer research study.
Office: 152A Hurley Hall
Phone: (574) 631-0301
Fax: (574) 631-4822