Research Overview

My research addresses central questions in social stratification and social demography, with a particular focus on life course inequality. I also advance computational social science by developing causal inference and machine learning not only as methodological tools but also as conceptual paradigms for how sociology generates knowledge. My work proceeds along three lines:

  • Examining how life disruptions act as stratifying forces that reinforce inequalities across the life course, particularly for women;
  • Investigating intra-group stratification with a focus on gender and racial inequality;
  • Advancing computational and demographic methods to estimate how life course processes contribute to inequality more precisely.

My research has appeared in peer-reviewed journals including the Journal for the Scientific Study of Religion (2023), the Journal of Marriage and Family (2022), and Social Science Research (2022).

I currently have six additional papers under review, four with revise-and-resubmit invitations, including one at Demography.

Key Research Projects

📄 Trajectory Stratification through Market, Family, and State

  • Sole-authored.
  • Under review at American Sociological Review
  • Examines how divorce triggers divergent institutional trajectories that structure long-term inequality, advancing the theory of trajectory stratification.
  • Keywords: Disruption, Stratification, Causal Machine Learning, Heterogeneity within Groups

📄 Differential Effects of College in Reducing COVID-19 Job Loss by Race and Skin Color

  • with Jennie E. Brand.
  • Revise & Resubmit at Demography
  • Uses causal mediation analysis to examine how college completion reduces COVID-19 job loss through access to high-skilled occupations, with differential effects by race and skin tone.
  • Keywords: Disruption, Stratification, Heterogeneity within Groups, Causal Machine Learning, Mediation

📄 Swapping Gender Traditionalism in South Korea

  • Sole-authored.
  • Published in Journal for the Scientific Study of Religion, 2023
  • Reveals how horizontal and vertical gender ideologies diverge within religious groups in Korea, challenging the assumption of unified gender traditionalism.
  • Received the Student Paper Award (Honorable Mention) from the ASA Sociology of Religion Section (2025).
  • Keywords: Heterogeneity within Groups, Religion, Gender

📄 Untangling Perceptions of Atypical Parents

  • with Natasha Quadlin, Long Doan, and Brian Powell.
  • Published in Journal of Marriage and Family, 2022
  • Explores how gendered caregiving norms shape perceptions of nontraditional families through survey experiments.
  • Keywords: Heterogeneity within Groups, Experiments, Family

📄 Deep Learning–Based G‑Computation for Life Course Sociology

  • Sole-authored.
  • In progress — part of M.S. thesis in Statistics and Data Science
  • Develops a deep learning–based method to estimate causal effects in longitudinal life course models, with a plausibility check for empirical positivity violations.
  • Keywords: Causal Machine Learning

📄 Causal Machine Learning for Sociology

  • with Jennie E. Brand.
  • Revise & Resubmit at Cologne Journal of Sociology and Social Psychology
  • Introduces causal machine learning as a deductive–inductive paradigm for theory-building in sociology.
  • Keywords: Causal Machine Learning

📄 Flexibly Detecting Effect Heterogeneity

  • with Jiahui Xi, Jennie E. Brand, and Tanvi Shinkre.
  • Revise & Resubmit at Sociological Methods & Research
  • Develops a flexible causal machine learning approach to detect treatment effect heterogeneity in causal mediation analysis, with application to college and poverty.
  • Keywords: Causal Machine Learning

📄 Researcher Reasoning Meets Computational Capacity

  • with Ian Lundberg and Jennie E. Brand.
  • Published in Social Science Research, 2022
  • Demonstrates how machine learning can support social science research and offers strategies to lower barriers to its adoption, with causal inference as one illustrative application.
  • Keywords: Machine Learning

📄 Estimating Multi-Annual Excess Deaths in the U.S.

  • with Patrick Heuveline.
  • Revise & Resubmit at European Journal of Population
  • Develops a demographic formula to estimate excess deaths, accounting for changes in population exposure over time, and reveals the long-term U.S. mortality disadvantage.
  • Keywords: Disruption, Formal Demography

In Development

📝 Causal Effects of Job Loss on Gendered Household Decisions

  • Sole-authored.
  • In progress – part of Ph.D. dissertation in Sociology
  • Estimates the causal impact of job loss on gendered decisions around labor force participation and domestic responsibilities, using longitudinal data and causal methods.
  • Keywords: Disruption, Causal Machine Learning, Gender

📝 Job Loss and Divorce in the U.S.

  • Sole-authored.
  • In progress – part of Ph.D. dissertation in Sociology
  • Examines how job loss influences relationship dissolution over time using longitudinal data and causal methods.
  • Keywords: Disruption, Causal Machine Learning, Family, Social Demography

🧪 Simulating Social Role Transitions Using Generative Models

  • Sole-authored.
  • Concept-stage project
  • Explores how generative AI can simulate household decision-making under life disruptions.
  • Keywords: Disruption, Generative AI, Experiments