​​​​Woojin Jung's research lies at the intersection of global poverty, social welfare policy, and Artificial  Intelligence (AI)/machine learning (ML) data science. Her work focuses on developing global poverty metrics and informing the distribution of social welfare programs in resource-constrained regions. By leveraging multimodal data (e.g., satellite imagery, social media, geographic attributes, and connectivity data), her research predicts poverty and creates high-resolution poverty maps in sub-Saharan Africa and Southeast Asia. Her research has recently expanded to identifying interpretable features, incorporating community inputs for feature selections, and explaining black box vision models. Most recently, her work focuses on imputing missing spatial data and optimizing resource allocation based on prediction. ​​​