Dr. Hong’s research aims at improving people’s capability of interacting with machine learning models and AI to derive better insights and decisions using data. In pursuing his research, he focuses on (1) building human-centered, interactive data acquisition environments that improve the data annotation process for collecting large-scale, accurate, and reliable data, (2) helping data scientists to build trustworthy machine learning models based on a deep understanding of their practices and needs, and (3) creating AI-driven interactive tools that can boost a single or a group of end-users task productivity.