Understanding individual choice behavior is critical for several disciplines that need to account for supply and demand dynamics. However, describing and predicting the behavior of agents is extremely challenging. Sophisticated mathematical models are required to better represent individuals’ decisions among mutually exclusive alternatives. The work of Dr. Daziano and his research group combines technical contributions in the search for more flexible choice models for engineering decision making – such as the derivation and analysis of estimators of advanced statistical models with less stringent assumptions over taste shocks – with empirical applications that necessitate a more flexible approach for providing more accurate predictions. The goal is to better understand the interplay of consumer behavior with engineering, investment, and policy choices for energy-efficient technologies.