Deep Learning Approaches to Demographic Forecasting

Date

-

Event Description

Paige Park is a PhD Candidate in Demography, University of California, Berkeley, where she also earned an MA in Statistics.

Her research lies at the intersection of demographic prediction, machine learning, and artificial intelligence. She is particularly interested in understanding why deep learning-based approaches improve demographic forecasts and what we can learn from them. More broadly, she is excited about the potential of AI and non-traditional data sources to improve our understanding of demographic processes.

Her research career began with sociological analyses of community, public policy, and immigrant outcomes in the US, leading to solo and co‑authored articles in journals such as Population Research and Policy Review and Sustainability. In her work, she combines her sociological background with her technical experience in statistics and machine learning to drive theory-informed innovation in demography.

Intended Audience

Research Community

Hosted by

The UC Berkeley Center on the Economics and Demography of Aging (CEDA)

Location

Hybrid

Event Type

Seminar