Woojin Jung’s research focuses on development aid policy as an instrument to alleviate global poverty. With her background in social welfare, public policy, and development engineering, she applies data science techniques to examine the relationship between poverty and aid in developing countries.
Her recent work combines deep learning with new sources of data, such as satellite imagery, to highlight latent features relating to the distribution of aid. She also explores the discrepancies between global poverty measures and the degree to which sectoral aid corresponds to the salient dimensions of poverty in emerging economies. Her work in this arena won the 2020 Outstanding Doctoral Dissertation award from the Society for Social Work and Research.
Jung teaches “Advanced Statistic Methods II: Generalized Linear Modeling and Other Advanced Methods,” a doctoral course. Prior to her current position at the School of Social Work, she held policy analyst positions in development agencies and worked with grassroots organizations in southeast Asia and Africa. Learn more about Jung.
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