Shenhao Wang is a fourth year Interdepartmental Doctoral Candidate between Department of Urban Studies and Planning and Computer Science and Artificial Intelligence Laboratory at MIT. His research interest is the interaction of machine learning, decision-making theories, and urban transportation applications. He is working on how to reframe traditional choice models as particular cases of deep learning, with an emphasis on the interpretability of “black box” deep neural networks in their applications to travel behavior. He also works on decision-making under uncertainty for the cases of autonomous vehicles and travel mode choice by using economics theory. He has side interests in transportation policies, such as car restriction policies in China. Shenhao Wang holds BA in Economics from Peking University and BA in architecture from Tsinghua university, Master of Science in Transportation, and Master of City Planning from MIT.