I joined Advertising Sciences after completing my Ph.D. at The University of Texas at Austin in 2011.

My research focuses on applications of machine learning in multi-agent systems, particularly in e-commerce settings. This research has been motivated by my participation in the Trading Agent Competition, where I have designed winning autonomous agents in both supply chain management and ad auction scenarios. My Ph.D. thesis explores 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.