Refugee Law

Refugee law research currently focuses on leveraging data-driven approaches to improve various aspects of refugee resettlement and legal aid. This includes using machine learning models, such as transformers and Bayesian networks, for tasks like predicting employment outcomes, optimizing resettlement placement, and streamlining legal intake processes through chatbots. These advancements aim to enhance efficiency, fairness, and transparency in refugee support systems, impacting both humanitarian operations and the legal field. The development of new datasets and methodologies for analyzing large-scale textual and visual data from sources like social media and news reports is also a key area of ongoing research.