My Research Journey

Growing up in South Korea, I witnessed how the Asian financial crisis disrupted families and reshaped entire life paths. These experiences made me attuned to how structural shocks don't just produce immediate harm—they can set people on diverging long-term trajectories, compounding inequality over time. Why do some individuals recover while others fall into long-term insecurity? And how do policies shape those divergent trajectories?

As I pursued graduate training in sociology, I found myself drawn to a deceptively simple but enduring question: How do life events accumulate to shape people’s futures? This question has guided me through diverse research projects on job loss, divorce, family transitions, and education—each framed by a broader concern with how risk and resilience are structured across the life course.

Yet as I deepened my substantive expertise, I kept encountering a methodological gap. Conventional tools in the social sciences often failed to capture the temporal, contingent, and compounding nature of the processes I was studying. In response, I began pursuing formal training in statistics and machine learning—not just to improve predictive power, but to build frameworks capable of modeling causal processes over time.

Today, my research bridges sociological theory with computational and statistical methods. I develop causal inference tools and deep learning models—such as Transformer-based g-computation frameworks—to analyze how life trajectories unfold under different institutional conditions. I aim to identify how disruptive events like divorce or job loss interact with policy regimes to shape long-term inequality, and to provide tools that support targeted interventions.

This integration of theory and method, of substance and structure, reflects what I value most about research: its ability to illuminate how inequality operates—not just in outcomes, but in trajectories. My goal is to develop work that contributes both to scientific understanding and to policy interventions.