Professor Ho's research centers on the design and analysis of human-in-the-loop systems, with a focus on eliciting and aggregating human-generated data. His research spans and draws from the fields of machine learning, algorithmic economics, optimization, and online behavioral social science. He is interested in developing realistic human behavior models and studying how the models influence the design of machine learning algorithms and incentive mechanisms.