David's research focuses on applications of machine learning in e-commerce settings. This research was motivated by his participation in the Trading Agent Competition, where he designed winning agents in supply chain management and ad auction scenarios. His dissertation explored methods by which agents in such settings can adapt to the behavior of other agents, with a particular focus on the use of transfer learning to learn quickly from limited interaction with these agents.