Jie Jian

I am a postdoctoral scholar at the Data Science Institute at the University of Chicago. My research develops interpretable probabilistic and machine-learning methods for network and tensor data, with a particular emphasis on latent variable models in both Bayesian and non-Bayesian settings. These methods are motivated by applications in brain imaging, climate science, international trade and relations, and linguistics. I completed my PhD in Statistics at the University of Waterloo. Before that, I earned an MSc in Applied and Computational Mathematics from Simon Fraser University and a BSc in Statistics from Huazhong University of Science and Technology.