I became a political scientist after receiving a Ph.D. in political science from the University of Iowa. As a political comparativist, my primary interest lies in exploring the government-mass relationship in the Chinese case and cross-nationally using political-psychological, political-linguistic, and political-economic approaches. My recent research focuses on how perceptive inequality, sociopolitical identities, and language choice influence citizens’ political cognition and responses to the government, institutions, and regime.
As a political methodologist, I am interested in developing methods for lab and survey experiments, spatial and network analyses, text analysis, and latent variable analysis. Some of my published and ongoing projects include adjusting matched-guise experiments, list experiments reuse, and the Dynamic Comparative Political Opinions (DCPO) for public-opinion analyses across surveys, countries, and time. And, I am an avid fan of data visualization.
As a faculty member, I have worked for Tsinghua since 2019. I teach such as public policy analysis, intro to political science, political method foundations, and big data analysis for governance. I am also the founder of “Learning R with Dr. Hu” year-long workshop and serve as the deputy directors of the Institute of Computational Social Science (清华大学计算社会科学平台) and the Center on Data and Governance at Tsinghua (清华数据治理中心). Since the spring of 2021, I’ve become a Github Campus Advisor and striven to promote version-control skills among students and anyone who are interested.