| Risk preference and adoption of autonomous vehicles S Wang, J Zhao Transportation research part A: policy and practice 126, 215-229, 2019 | 153 | 2019 |
| Choice modelling in the age of machine learning-Discussion paper S van Cranenburgh, S Wang, A Vij, F Pereira, J Walker Journal of Choice Modelling 42, 100340, 2022 | 122* | 2022 |
| Deep neural networks for choice analysis: Extracting complete economic information for interpretation S Wang, Q Wang, J Zhao Transportation Research Part C: Emerging Technologies 118, 102701, 2020 | 106 | 2020 |
| Deep neural networks for choice analysis: Architecture design with alternative-specific utility functions S Wang, B Mo, J Zhao Transportation Research Part C: Emerging Technologies 112, 234-251, 2020 | 91 | 2020 |
| Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark S Wang, B Mo, S Hess, J Zhao arXiv preprint arXiv:2102.01130, 2021 | 50 | 2021 |
| Deep neural networks for choice analysis: A statistical learning theory perspective S Wang, Q Wang, N Bailey, J Zhao Transportation Research Part B: Methodological 148, 60-81, 2021 | 45* | 2021 |
| Uncertainty quantification of sparse travel demand prediction with spatial-temporal graph neural networks D Zhuang, S Wang, H Koutsopoulos, J Zhao Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 41 | 2022 |
| Multitask learning deep neural networks to combine revealed and stated preference data S Wang, Q Wang, J Zhao Journal of choice modelling 37, 100236, 2020 | 36 | 2020 |
| Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks S Wang, B Mo, J Zhao Transportation research part B: methodological 146, 333-358, 2021 | 34 | 2021 |
| The relationship between ridehailing and public transit in Chicago: A comparison before and after COVID-19 P Meredith-Karam, H Kong, S Wang, J Zhao Journal of Transport Geography 97, 103219, 2021 | 30 | 2021 |
| Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models Y Zheng, S Wang, J Zhao Transportation Research Part C: Emerging Technologies 132, 103410, 2021 | 27 | 2021 |
| The distributional effects of lotteries and auctions—License plate regulations in Guangzhou S Wang, J Zhao Transportation Research Part A: Policy and Practice 106, 473-483, 2017 | 25 | 2017 |
| Uncertainty quantification of spatiotemporal travel demand with probabilistic graph neural networks Q Wang, S Wang, D Zhuang, H Koutsopoulos, J Zhao IEEE Transactions on Intelligent Transportation Systems, 2024 | 21 | 2024 |
| Measuring policy leakage of Beijing’s car ownership restriction Y Zheng, J Moody, S Wang, J Zhao Transportation Research Part A: Policy and Practice 148, 223-236, 2021 | 21 | 2021 |
| Transportation policy profiles of Chinese city clusters: A mixed methods approach J Moody, S Wang, J Chun, X Ni, J Zhao Transportation Research Interdisciplinary Perspectives 2, 100053, 2019 | 20 | 2019 |
| ST-GIN: An uncertainty quantification approach in traffic data imputation with spatio-temporal graph attention and bidirectional recurrent united neural networks Z Wang, D Zhuang, Y Li, J Zhao, P Sun, S Wang, Y Hu 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | 11 | 2023 |
| Spatiotemporal graph neural networks with uncertainty quantification for traffic incident risk prediction X Gao, X Jiang, D Zhuang, H Chen, S Wang, J Haworth arXiv preprint arXiv:2309.05072, 2023 | 11 | 2023 |
| Deep hybrid model with satellite imagery: How to combine demand modeling and computer vision for travel behavior analysis? Q Wang, S Wang, Y Zheng, H Lin, X Zhang, J Zhao, J Walker Transportation Research Part B: Methodological 179, 102869, 2024 | 8 | 2024 |
| Fairness-enhancing deep learning for ride-hailing demand prediction Y Zheng, Q Wang, D Zhuang, S Wang, J Zhao IEEE Open Journal of Intelligent Transportation Systems, 2023 | 8 | 2023 |
| Cooperative bus holding and stop-skipping: A deep reinforcement learning framework J Rodriguez, HN Koutsopoulos, S Wang, J Zhao Transportation Research Part C: Emerging Technologies 155, 104308, 2023 | 7 | 2023 |
Jinhua ZhaoProfessor of Cities and Transportation, Massachusetts Institute of TechnologyDirección de correo verificada de mit.edu