Sun Y, Hu W, Zhou D, Baichuan Mo, Fu K, Che Z, et al. Alleviating Data Sparsity Problems in Estimated Time of Arrival via Auxiliary Metric Learning. IEEE Transactions on Intelligent Transportation Systems. 2022.

Zhuang D, Shenhao Wang, Haris Koutsopoulos, Jinhua Zhao. Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks.; 2022.

Shenhao Wang, Qingyi Wang, Nate Bailey, Jinhua Zhao. Deep Neural Networks for Choice Analysis: A Statistical Learning Theory Perspective. Transportation Research Part B. 2021.

Yunhan Zheng, Shenhao Wang, Jinhua Zhao. Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models. Transportation Research Part C. 2021.

Yunhan Zheng, Joanna Moody, Shenhao Wang, Jinhua Zhao. Measuring policy leakage of Beijing’s car ownership restriction. Transportation Research Part A: Policy and Practice. 2021.

Meredith-Karam P, Hui Kong, Shenhao Wang, Jinhua Zhao. The Relationship between Transportation Network Companies and Public Transit in Chicago: a comparison before and after COVID-19 shutdowns. Journal of Transport Geography. 2021.

Shenhao Wang, Baichuan Mo, Jinhua Zhao. Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks. Transportation Research Part B. 2021.

Shenhao Wang, Baichuan Mo, Jinhua Zhao. Deep Neural Networks for Choice Analysis: Architecture Design with Alternative-Specific Utility Functions. Transportation Research Part C. 2020.

Shenhao Wang, Qingyi Wang, Jinhua Zhao. Deep Neural Networks for Choice Analysis: Extracting Complete Economic Information for Interpretation. Transportation Research Part C: Emerging Technologies. 2020.

Yunhan Zheng, Joanna Moody, Shenhao Wang, Jinhua Zhao. Measuring Policy Leakage of Beijing's Car Ownership Restriction in Neighboring Cities. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.

Shenhao Wang, Qingyi Wang, Jinhua Zhao. Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data. Journal of Choice Modelling. 2020.

Shenhao Wang, Baichuan Mo, Jinhua Zhao. Predicting Travel Mode Choice with 86 Machine Learning Classifiers: An Empirical Benchmark Study. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.

Shenhao Wang, Joanna Moody, Jinhua Zhao. What prompts the adoption of car restriction policies among Chinese cities. International Journal of Sustainable Transportation. 2020.

Shenhao Wang. Deep Neural Networks for Choice Analysis. Vol PhD.; 2019.

Shenhao Wang, Qingyi Wang, Jinhua Zhao. Deep Neural Networks for Choice Analysis: A Statistical Learning Theory Perspective. Working Paper. 2019.

Shenhao Wang, Jinhua Zhao. Risk Preference and Adoption of Autonomous Vehicles. Transportation Research Part A. 2019.

Joanna Moody, Shenhao Wang, Jungwoo Chun, Xuenan Ni, Jinhua Zhao. Transportation Policy Profiles of Chinese City Clusters: A Mixed Method Approach. Transportation Research Interdisciplinary Perspectives. 2019.

Shenhao Wang, Jinhua Zhao. How Risk Preferences Influence the Usage of Autonomous Vehicles. In: Transportation Research Board 97th Annual Meeting. Washington, D.C.; 2018.

Shenhao Wang, Jinhua Zhao. Trajectories of Urban Development and Motorization: Clustering 287 Chinese Cities. In: Transportation Research Board 97th Annual Meeting. Washington, D.C.; 2018.

Shenhao Wang. Automobile Regulations in China Examined from a Behavioral Perspective. Vol Master in City Planning, Master of Science in Transportation. Cambridge, MA: Massachusetts Institute of Technology; 2017.

Shenhao Wang, Jinhua Zhao. Distributional Effects of Lotteries and Auctions —License Plate Regulations in Guangzhou. Transportation Research Part A: Policy and Practice. 2017;106:473-483.

Shenhao Wang, Jinhua Zhao. Risk Attitude in Choosing Between Lottery And Auction In License Plate Regulations.; 2017.