Xingyun Wu 吴星韵

Ph.D. in Sociology,
Johns Hopkins University

Postdoctoral Fellow,
Research Hub of Population Studies,
The University of Hong Kong

Areas of Specialization:
Social inequality, work and family, population health
Quantitative and computational methods

Contact: xywu_soc@outlook.com

My up-to-date CV here

My GitHub here

My example code in Python, R, and Stata

About Me

I am a sociologist and social demographer, who recently joined the Research Hub of Population Studies at The University of Hong Kong and previouly worked as research assistant and student affiliate at the Hopkins Population Center. My research focuses on social inequality, work and family, and population health, with a strong foundation in quantitative and computational methods.

Research

My dissertation centers on socially structured activity-time allocation in daily life, exploring how work, family, and personal domains interact to reproduce gender and class inequality. I conceptualized individuals' daily life as a system of the three domains, with interpersonal interdependence within family. Methodologically, I integrate machine learning with classical statistical methods to overcome empirical limitations and expand the analytic potential of nationally representative datasets, including the American Time Use Survey, the Current Population Survey, and the O*NET occupational database. My work seeks to understand how structural inequality in the labor market and family manifest in individuals’ everyday decisions and behaviors, and shows how equitable social environments may support more sustainable and inclusive social outcomes for the whole population.

In additional to my independent research, I have also collaborated on interdisciplinary research projects on the following topics:

• Adolescent health, substance-use, and preventive care receipts
• Population and places in response to environmental hazards
• Student-AI interaction in higher education

These projects complement my dissertation research and reflect my broader research interests in how structural forces shape individual opportunities and behaviors, as well as population-level outcomes. My roles in these research projects include statistical modeling, research paper writing, data collection and database management, as well as visualization across diverse data types. I have worked with a wide range of data, including household- or individual-based survey data, national and county-level population and geospatial data, and structured and unstructured textual data. I developed strong programming skills, workflow management, interdisciplinary collaboration, and the production of timely, high-quality research outputs along the process.

Teaching

I welcome opportunities to teach in various forms on my substantive areas of focus and methodology. My prior teaching experience mainly focused on research methods in social science, introduction to social statistics, and applied computational social science. I am happy to extend my teaching to substantive topics in social inequality and social demography, including work and family, gender, and population health in the future.