Hang works on machine learning, natural language processing, and computational social science. He is interested in building socially-aware, interpretable, robust, and fair NLP models. Specifically, his projects are related to language variation, opinion mining, and event detection and summarization. Before MIT, he did his undergrad at Emory in Computer Science and Linguistics and obtained his M.S. degree in Symbolic Systems at Stanford.