Woojin Jung

Dr. Jung's primary field of study lies at the intersection of global poverty, socioeconomic development, and data science. The overarching goal of Dr. Jung's research is to impact the approaches to characterize global poverty and shape global/social transfers in resource-constrained settings. Trained as a social welfare scholar, policy analyst, and development engineer, her research is motivated by the desire to inform effective anti-poverty interventions. Dr. Jung's scholarship centers on three main areas for generating questions: 

• Poverty measurement on a global scale
• The relevance of community development in response to regional poverty
• Informing the design of social welfare policies

As a publicly engaging scholar, she assists key development institutions in designing social protection policies and programs. The global economic and health risks highlight the need for efficient and systematic targeting to reach the most vulnerable populations. To address this issue, her recent work in Southeast Asia and Sub-Saharan Africa aims to generate robust wealth metrics at a granular level. Her studies leverage features from new data sources, such as satellite imagery and social media, which is extracted and analyzed by artificial intelligence (AI)/ machine learning (ML) techniques at a policy-relevant spatial unit.

Dr. Jung's current projects are funded by Microsoft's AI for Humanitarian Action and received data support from Google, Twitter, and Planet Scope. She serves as PI for studies in the Republic of the Congo and Zambia. Dr. Jung works via a tripartition collaboration between governments, including the Ministry of Community Development and Social Services in Zambia, and the Institut Géographique National in Congo; international organizations, such as the World Food Programme; and non-government organizations, such as Innovations for Poverty Action.  Learn more about Dr. Jung's work in the Republic of Congo and her project in Zambia.

Social Welfare Policy and Services I

Advanced Statistic Methods II: Generalized Linear Modeling and Other Advanced Methods

Research Methods I

Research Methods II

Jung, W., Kim, A., & Chear, C. (2024, July 17). Data Science and Social Work. Encyclopedia of Social Work. https://doi.org/10.1093/acrefore/9780199975839.013.1649

Bukhari, M. H., Shad, M. Y., Nguyen, U. D. T., Trevino, J. A. Jung, W. C., Haque, U, (2023). A Bayesian spatiotemporal approach to modelling arboviral diseases in Mexico, Trans R Soc Trop Med Hyg 2023; 0: 1–9, https://doi.org/10.1093/trstmh/trad064

Jung, W. (2023). Mapping community development aid: Spatial analysis in Myanmar. World Development, 164  https://doi.org/10.1016/j.worlddev.2022.106124
50 day-free access

Jung, W. (2022) The Discrepancy Between Two Approaches to Global Poverty: What Does it Reveal?. Social Indicators Research. https://doi.org/10.1007/s11205-021-02866-6

Jung, W. (2021). Becoming One: Religion, Development, and Environmentalism in a Japanese NGO in Myanmar. By Chika Watanabe. Pacific Affairs, 94(4), 781-783.

Jung, W. (2020). Two Models of Community-centered Development in Myanmar. World Development, 136. https://doi.org/10.1016/j.worlddev.2020.105081  

Jung, W. (2020). Using data science to strengthen the social safety net: Predicting risk for Medicare and Medicaid insurers. Journal of Governmental Studies. 26(2) https://dx.doi.org/10.19067/jgs.2020.26.2.29 

Organista, K. C., Jung, W., & Neilands, T. (2020). A structural-environmental model of alcohol and substance-related sexual HIV risk in Latino migrant day laborers. AIDS and Behavior. https://doi.org/10.1007/s10461-020-02876-4

Wu. C-F, Chang, Y-L., Rhodes, E., Musaad, S. & & Jung, W. (2020), Work-Hour trajectories and associated socioeconomic characteristics among single-mother families. Social Work Research. 44(1), 47-57. https://doi.org/10.1093/swr/svz029

Organista, K., Jung, W., & Neilands, T.  (2019). Working and living conditions and psychological distress in Latino Migrant Day Laborers. Health Education & Behavior, 46(4), 637-647. https://doi.org/10.1177/1090198119831753

Kim, P. H., & Jung, W. (2018). Ownership and planning capacity in the Asian-style development cooperation: South Korean Knowledge Sharing Program to Vietnam. Korea Observer, 49(2), 349-368. https://doi.org/10.29152/KOIKS.2018.49.2.349

Kharas, H., Makino, K., & Jung, W. (Eds.). (2011). Catalyzing development: a new vision for aid. Brookings Institution Press.

Rutgers Research Feature: Focus on Faculty with Assistant Professor Woojin Jung

Assistant Professor Woojin Jung Receives Research Council Award

Assistant Professor Woojin Jung Receives Microsoft Azure Grant

"Development Engineering Scholar Woojin Jung Finds Significant Discrepancies in Global Poverty Measures" in Blum Center for Developing Economies. https://blumcenter.berkeley.edu/news-posts/development-engineering-scholar-woojin-jung-finds-significant-discrepancies-in-global-poverty-measures/

Exploring Scalable Multimodal Approaches to Identify Vulnerable Populations in the Congo 
Woojin Jung, PhD, MPP, MSW, Rutgers School of Social Work
Grant Category: Research
Collaborative Partners: Microsoft, World Food Programme
This project will use artificial intelligence technologies to more accurately and rapidly identify areas of extreme poverty in the Republic of the Congo, informing humanitarian responses to the country’s surging food insecurity in the wake of COVID-19. The research will incorporate daytime satellite imagery, nighttime luminosity, and social media data to create algorithms that estimate the wealth and livelihood of geographic regions. The robust and objective information that is produced will allow for more precise targeting of social safety net programs.

2023-2024 (Grant Amount: $50,000), “Detecting Human-Interpretable Features from Satellite Imagery to Support Poverty Mapping,” The Office for the Vice Provost for Research’s ML/AI Pilot Seed Grant, PI: Woojin Jung https://newbrunswick.rutgers.edu/chancellor/research/seed-funding-projects

2023-2024 (Grant Amount: $25,000), “Improving Distribution of Food Aid via Trustworthy Multimodal Poverty Prediction,” Cyberinfrastructure & AI for Science and Society Seed Grant, PI: Woojin Jung