Lizhi is a PhD student in the SAMBa CDT at the University of Bath. He works on developing statistical inference techniques for network analysis, supervised by Dr. Tiago P. Peixoto. Lizhi obtained a MASt in Mathematical Statistics from University Cambridge, dual bachelor degrees majoring in Applied Mathematics and Statistics from Donghua University (Shanghai, China) and Uni of Strathclyde (Glasgow, UK). He completed a summer internship at GlaxoSmithKline where he worked on text-mining techniques for constructing gene-regulatory networks.
Recent years have witnessed a surge of new approaches for community detection based on Bayesian inference of generative network models. However, most existing methods do not incorporate a variety of realistic features that are known to exist in many empirical settings. In Lizhi’s doctoral project, he aims to develop a series of models and associated inference algorithms that are capable of extracting large-scale structures from network data, in a manner that includes realistic assumptions (such as preferred mixing patterns, growth dynamics, spatial embedding, etc.). The main methodology will be the Bayesian construction of generative network models, as well as algorithmic inference techniques such as MCMC, expectation-maximisation and variational methods.