Woojin Jung

 Researcher of Poverty & Development
Dr. Woojin Jung

Global Poverty & Aid

Dr. Jung’s research focuses on development aid policy as an instrument to alleviate global poverty. She applies data science techniques to examine the relationship between poverty and aid, particularly in fragile states.

Recent Honors

recipient of
Microsoft's Azure Grant
AI for Humanitarian Action Project Initiatives

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The grant will support Dr. Jung’s latest project: "Exploring scalable multimodal approaches to identify vulnerable populations in the Congo."

recipient of
Rutgers Research Council
Collaborative Multidisciplinary Award

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The grant will support Dr. Jung’s latest project: "Developing AI-informed vulnerability index to target Food Security Pack(FSP) program in Zambia"

recipient of
Rutgers Global Health Institute
Global Health Seed Grants

The grant will support Dr. Jung’s latest project: "Exploring scalable multimodal approaches to identify vulnerable populations in the Congo."

Learn More
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recipient of the 2020

Society for Social Work and Research

Outstanding Social Work Doctoral Dissertation Award 

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“Combating Poverty through Aid:

A Critical Analysis of Alternative Models.” 

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recipient of the 2016

Korea Association of International Development Cooperation 

Highest Honors in Graduate Research Award 

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Recent Avtivities

Invited Presenter at the

 Korea Association of

International Development & Cooperation (KAIDEC)

& Seoul National University Asia Center

Seoul, Korea (July 2020)

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"Combining Satellite Imagery with Deep Learning to Predict Poverty in Data-Sparse Contexts"

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Invited Presenter at the

 Institute of Governmental Studies

Department of Public Administration

Korea University

Seoul, Korea (January 2020)

Korea University Colloquium

"Using Machine Learning to Evaluate Aid Distribution"

Recent Publications

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New Journal Article Published in: 

World Development (2020) 

"Two Models of Community-Centered Development in Myanmar"

New Journal Article Published in: 

Journal of Governmental Studies (2020) 

"Using Data Science to Strengthen the Social Safety Net: Prediction Risk for Medicare and Medicaid Insurers"

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Research  Areas

 

COMMUNITY

AID

TECHNOLOGY

POLICY