• Lifespan Social Production
• Healthy Aging
• Time Series Data Modeling

Lifespan Social Production
The Lifespan Social Production project examines the economic value of unpaid activities that sustain society across different stages of life. It quantifies contributions such as unpaid childcare, volunteering, care for older adults and people with disabilities, and civic participation, showing that these forms of social production represent a substantial share of national economic output despite often being overlooked in conventional economic measures. By translating time spent on these activities into economic terms, the research highlights the often-invisible infrastructure that supports communities and challenges the common narrative that older adults are primarily economic dependents. Instead, the project demonstrates their significant contributions and provides an evidence-based foundation for policies that invest in childcare, strengthen volunteer systems, and recognize caregiving as a core component of economic infrastructure.

Large-Scale Individual-Centered Longitudinal Data Modeling for Healthy Longevity
This project aims to address the heterogeneity of aging by shifting research from population averages to individual-centered analysis. Traditional evidence for prevention and lifestyle guidance often relies on group-level findings that obscure meaningful within-person dynamics. This project advances a new paradigm in healthy longevity research by modeling individuals separately using large-scale multimodal longitudinal data which include wearable sensor data, self-reports, and digital behavioral traces while individuals retain control over their own data. The project goal is to demonstrate that person-specific models capture individual aging trajectories more accurately than aggregating distributed data into population models. Using advanced time-series analysis and machine learning to analyze multivariate temporal data, the research emphasizes within-individual dynamics and signal interdependencies over time, aiming to produce more precise and actionable insights for personalized prevention and intervention.