Adviser(s):
Roman Garnett, Jacob Montgomery
Bio:
I am a second-year PhD student in Division of Computational Data Science at WashU. Prior to that, I received my BS in Computer Science at University of Michigan, class of 2019. I also earned a BSE in Electrical & Computer Engineering at Shanghai Jiao Tong University in 2019, under the UM-SJTU Joint Institute.
Research interests and current project:
My research interest lies in the interaction between Bayesian machine learning and political methodology, including but not limited to election forecasting and causal inference.
My current project is Bayesian difference in difference with mult-task gaussian process.
My paper ‘Polls, Context, and Time A Dynamic Bayesian Forecasting Model for US Senate Elections’ is under R&R of Journal of Political Analysis.
Why did you decide to pursue your PhD at WashU?
I decided to pursue my PhD at WashU because of its strong academic environment and amazing campus.