Publications

By June 2024, Dr. Ke have co-authored 38 articles in peer-reviewed journals. His papers have been cited by more than 4,200 times and his H-Index is 25 according to Google Scholar. He was ranked top 2% scientists by standardized career year-adjusted citations calculated by Ioannidis, John P.A., Stanford University and Elsevier in 2023.

  • Ke J., Yang H., Wang H., and Yin Y., 2023. Supply and demand management of ride-sourcing markets, Elsevier.
  • (* indicates the corresponding author, underline refers to the Ph.D., M.Phil. visiting students, postdoc and research assistants of Dr. Jintao Ke)
  • Zhou, Y., Ke, J.*, Yang, H., and Guo, P., 2024. Platform integration for ride-sourcing markets with heterogeneous customers. Transportation Research Part B, in press.
  • Wong, R. C. P., Ke, J., Szeto, W. Y., and Mak, P. L., 2024. Multiple shared mobility services under competition: Empirical evidence for public acceptance and policy insights to sustainable transport. International Journal of Sustainable Transportation, 1–14.
  • Guo, S., Deng, B., Chen, C., Ke, J., Wang, J., Long, S., Xu, K., 2024. Seeking in ride-on-demand service: a reinforcement learning model with dynamic price prediction. IEEE Internet of Things Journal, in press.
  • Ke, J., Wang, H., Masoud, N., Schiffer, M., Corria, G., 2024. Editorial: Emerging on-demand passenger and logistics systems: Modelling, optimization, and data analytics. Transportation Research Part C: Emerging Technologies, 161, 104574.
  • Wang, Z., Ke, J., and Li, S., 2024. Planning and operation of ride-hailing networks with a mixture of level-4 autonomous vehicles and for-hire human drivers. Transportation Research Part C: Emerging Technologies, 160, 104541.
  • Ke, J., Wang, C., Li, X., Tian, Q., and Huang, H., 2024. Equilibrium analysis for on-demand food delivery markets. Transportation Research Part E: Logistics and Transportation Review, 184, 103467.
  • Chen, Z., Miu, Y., Ke, J.*, and He, Q., 2024. Operations and regulations for a ride-sourcing market with a mixed fleet of human drivers and autonomous vehicles. Transportation Research Part C: Emerging Technologies, 160, 104519.
  • Chen, W., Gu, D., and Ke, J., 2023. Real-time ergonomic risk assessment in construction using a co-learning-powered 3d human pose estimation model. Computer-Aided Civil and Infrastructure Engineering, 1–17, https://doi.org/10.1111/mice.13139.
  • Feng, S., Wei, S., Zhang, J., Li, Y., Ke, J., Chen, G., ... and Yang, H., 2023. A macro–micro spatio-temporal neural network for traffic prediction. Transportation Research Part C: Emerging Technologies, 156, 104331.
  • Liang, J., Ke, J.*, Wang, H., Ye, H., Tang, J., 2023. A Poisson-based Distribution Learning Framework for Short-term Prediction of Food Delivery Demand Ranges. IEEE Transactions on Intelligent Transportation System, in press.
  • Zhu, Z., Xu, M., Ke, J., Yang, H., and Chen, X. M., 2023. A Bayesian clustering ensemble Gaussian process model for network-wide traffic flow clustering and prediction. Transportation Research Part C: Emerging Technologies, 148, 104032.
  • Li, X., Yang, H., and Ke, J.*, 2022. Booking cum rationing strategy for equitable travel demand management in road networks. Transportation Research Part B: Methodological, 167, 261−274.
  • Vignon, D., Yin, Y., and Ke, J., 2023. Regulating the ride-hailing market in the age of uberization. Transportation Research Part E: Logistics and Transportation Review, 169, 102969.
  • Feng, S., Ke, J.*, Xiao, F., and Yang, H., 2022. Approximating a ride-sourcing system with block matching. Transportation Research Part C: Emerging Technologies, 145, 103920.
  • Ke, J., Yang, H., Chen, X.*, and Li, S., 2022. Coordinating supply and demand in ride-sourcing markets with pooling service and traffic congestion externality. Transportation Research Part E: Logistics and Transportation Review, 166, 102887.
  • Zhou, Y., Yang, H., and Ke, J.*, 2022. Price of competition and fragmentation in ride-sourcing markets. Transportation Research Part C: Emerging Technologies, 143, 103851.
  • Qin, X., Ke, J., Wang, X., Tang, Y., & Yang, H., 2022. Demand management for smart transportation: A review. Multimodal Transportation, 1(4), 100038.
  • Wei, S., Feng, S., Ke, J.*, and Yang, H.,2022. Calibration and validation of matching functions for ride-sourcing markets. Communications in Transportation Research, 2, 100058.
  • Feng, S., Duan, P., Ke, J.*, and Yang H., 2022. Coordinating ride-sourcing and public transport services with a reinforcement learning approach. Transportation Research Part C: Emerging Technologies, 138, 103611.
  • Zhou, Y., Yang, H., Ke, J.*, Wang, H., and Li, X., 2022. Competition and third-party platform-integration in ride-sourcing markets. Transportation Research Part B: Methodological, 159, 76−103.
  • Feng, S., Ke, J.*, Yang, H., Ye, J., 2022. A multi-task matrix factorized graph neural network for co-prediction of zone-based and OD-based ride-hailing demand. IEEE Transactions on Intelligent Transportation Systems, 23(6), 5704−5716, DOI: 10.1109/TITS.2021.3056415.
  • Ke, J., Xiao, F.*, Yang, H. and Ye, J., 2022. Learning to delay in ride-sourcing systems: a multi-agent deep reinforcement learning framework. IEEE Transactions in Knowledge and Data Engineering, 34(5), 2280−2292, DOI: 10.1109/TKDE.2020.3006084.
  • Zhao, Y., and Ke, J.*, 2021. The impact of shared mobility services on housing values near subway stations. Transportation Research Part D: Transport and Environment, 101, 103097.
  • Ke, J., Li, X.*, Yang, H., and Yin, Y., 2021. Pareto-efficient solutions and regulations of congested ride-sourcing markets with heterogeneous demand and supply. Transportation Research Part E: Logistics and Transportation Review, 154, 102483.
  • Urata, J., Xu, Z., Ke, J., Yin, Y., Wu, G., Yang, H., and Ye, J., 2021. Learning ride-sourcing drivers’ customer-searching behavior: A dynamic discrete choice approach. Transportation Research Part C: Emerging Technologies, 130, 103293.
  • Zhu, Z., Ke, J.*, and Wang, H., 2021. A mean-field Markov decision process model for spatial-temporal subsidies in ride-sourcing markets. Transportation Research Part B: Methodological, 150, 540−565.
  • Yang, L., Ao, Y., Ke, J., Lu, Y., and Liang, Y., 2021.To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults. Journal of Transport Geography, 94, 103099.
  • Vignon, D., Yin, Y., and Ke, J., 2021. Regulating ride-sourcing services with product differentiation and congestion externality. Transportation Research Part C: Emerging Technologies, 127, 103088.
  • Ke, J., Feng, S., Zhu, Z.*, Yang, H., and Ye, J., 2021. Joint predictions of ride-hailing demands for multiple service modes with a deep multi-task multi-graph learning framework. Transportation Research Part C: Emerging Technologies, 127, 103063.
  • Ke, J., Zhu, Z.*, Yang, H., and He, Q., 2021. Equilibrium analyses and operational designs of a coupled market with substitutive and complementary ride-sourcing services to public transits. Transportation Research Part E: Logistics and Transportation Review, 148, 102236.
  • Ke, J., Zheng, Z.*, Yang, H., and Ye, J., 2021. Data-Driven analysis of matching probability, routing Distance and detour distance in on-demand ride-pooling services. Transportation Research Part C: Emerging Technologies, 124, 102922.
  • Ke, J., Qin, X.*, Yang, H., Zheng, Z., Zhu, Z., and Ye, J., 2021. Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network. Transportation Research Part C: Emerging Technologies, 122, 102858.
  • Ke, J.*, Yang, H. and Zheng, Z., 2020. On ride-pooling and traffic congestion. Transportation Research Part B: Methodological, 142, 213−231.
  • Ke, J., Yang, H., Li, X., Wang, H.*, and Ye, J., 2020. Pricing and equilibrium in on-demand ride-pooling markets. Transportation Research Part B: Methodological, 139, 411−431.
  • Chen, X., Zheng, H., Ke, J., and Yang, H.*, 2020. Dynamic optimization strategies for on-demand ride services platform: surge pricing, commission rate, and incentives. Transportation Research Part B: Methodological, 138, 23−45.
  • Zhu, Z., Qin, X.*, Ke, J., Zheng, Z. and Yang, H., 2020. Analyzing the Impact of Ridesplitting Programs on Multi-Modal Commute Behavior based on a Network Model. Transportation Research Part A: Policy and Practice, 132, 713−727.
  • Yang, H. Qin, X., Ke, J.* and Ye, J., 2019. Optimizing matching time interval and matching radius in on-demand ride-sourcing markets. Transportation Research Part B: Methodological, 131, 84−105.
  • Ke, J., Cen, X., Yang, H., Chen, X.*, and Ye, J., 2019. Modelling drivers’ working and recharging schedules in a ride-sourcing market with electric vehicles and gasoline vehicles. Transportation Research Part E: Logistics and Transportation Review, 125, 160−180.
  • Ke, J., Yang, H., Zheng, H., Chen, X.*, Jia, Y., Gong, P., and Ye, J., 2019. Hexagon-based convolutional neural network for supply-demand forecasting of ride-sourcing services. IEEE Transactions on Intelligent Transportation Systems, 20(11), 4160−4173.
  • Ke, J., Zhang, S., Yang, H. and Chen, X.*, 2018. PCA-based missing information imputation for real-time crash likelihood prediction under imbalanced data. Transportmetrica A: Transport Science, 15(2), 872−895.
  • Yang, H., Ke, J.*, and Ye, J., 2018. A universal distribution law of network detour ratios. Transportation Research Part C: Emerging Technologies, 96, 22−37.
  • Ke, J., Zheng, H., Yang, H. and Chen, X.M., 2017. Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach. Transportation Research Part C: Emerging Technologies, 85, 591−608.
  • Shao, C., Yang, H., Zhang, Y. and Ke, J., 2016. A simple reservation and allocation model of shared parking lots. Transportation Research Part C: Emerging Technologies, 71, 303−312.
  • (The most prestigious series of symposia in theoretical transportation research, only about 35 papers are selected through a two-stage peer review process for each symposium. From 2011 or the 19th ISTTT, all selected papers are published in Transportation Research Series)
  • Zhu, Z., Ke, J.*, and Wang, H., 2021. A mean-field markov decision process for ride-sourcing modeling: optimization of spatial subsidy and idle vehicle relocation. Selected for an oral presentation by the 24th International Symposium on Transportation and Traffic Theory (ISTTT24), and published in Transportation Research Part B: Methodological.
  • Zhang K., Ke J., Wang H. and Yin Y., 2023. Operational strategy design for on-demand food delivery services. Proceedings of the 27th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2023: Transport and Equity, Hong Kong, December 11–12, 2023.
  • Chen W., Ke J., Yang L. and Chen X., 2023. Scaling laws of dynamic high-capacity ride-sharing. Proceedings of the 27th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2023: Transport and Equity, Hong Kong, December 11–12, 2023.
  • Liang J. and Ke J., 2023. Understanding users’ cancellation behaviors in online food delivery markets: A reference-dependent survival analysis. Proceedings of the 27th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2023: Transport and Equity, Hong Kong, December 11–12, 2023.
  • Wang J., Liu X., and Ke J., 2023. Joint optimization of pricing and routing for dynamic ride-sharing considering order cancellations. Proceedings of the 27th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2023: Transport and Equity, Hong Kong, December 11–12, 2023.
  • Chen T., Shen Z., Feng S., and Ke J., 2023. TEB: A time series model for on-demand e-hailing matching in the broadcasting mode. Proceedings of the 27th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2023: Transport and Equity, Hong Kong, December 11–12, 2023.
  • Wang C. and Ke J., 2023. Modelling a ride-sourcing market with a third-party platform integrator under batch matching mechanisms. Proceedings of the 27th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2023: Transport and Equity, Hong Kong, December 11–12, 2023.
  • Zhang K. and Ke J., 2023. A modeling framework for the three-sided network equilibrium in on-demand food service. Proceedings of the 27th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2023: Transport and Equity, Hong Kong, December 11–12, 2023.
  • Liang J., Ke J., Ye H., Wang H. and Tang J., 2022. A Poisson-Based Distribution Learning Framework for Short-Term Prediction of Food Delivery Demand Ranges. Proceedings of the 26th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2022: Great Transportation, Hong Kong, December 12−13, 2022.
  • Feng S., Wei S., Ke J., and Yang H., 2022. A macro-micro spatio-temporal neural network for traffic prediction. Proceedings of the 26th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2022: Great Transportation, Hong Kong, December 12−13, 2022.
  • Zhou Y., Ke J., and Yang H., 2022. Price of competition and fragmentation in ride-sourcing markets. Proceedings of the 26th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2022: Great Transportation, Hong Kong, December 12−13, 2022.
  • Feng S., Chen T., Zhang Y., Ke J., and Yang H., 2022. An open-source simulator for ride-sourcing market based on real-world road network. Proceedings of the 26th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2022: Great Transportation, Hong Kong, December 12−13, 2022.
  • Zhu, Z., Ke, J.*, and Wang, H., 2021. A mean-field markov decision process for ride-sourcing modeling: optimization of spatial subsidy and idle vehicle relocation. Selected for an oral presentation by the 24th International Symposium on Transportation and Traffic Theory (ISTTT24), and published in Transportation Research Part B: Methodological.
  • Feng, S., Ke, J., and Yang, H., 2021. Coordinating ride-sourcing and public transport services with a reinforcement learning approach. Proceedings of the 25th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2021: Sustainable Mobility, Hong Kong, December 9−10, 2021.
  • Ke, J., Li, X., and Yang, H., 2021. Pareto-efficient regulation in ride-sourcing markets. Proceedings of the 25th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2021: Sustainable Mobility, Hong Kong, December 9−10, 2021.
  • Ke, J., Zheng, Z., Yang, H., and Ye, J., 2021. Universal laws of matching probability, routing distance and detour distance in on-demand ride-splitting services. Proceedings of the 25th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2021: Sustainable Mobility, Hong Kong, December 9−10, 2021.
  • Qin, X., Wu, Y., Liu, W., Ke, J., and Yang, H., 2021. Integrated strategies for repositioning, upgrading and pricing in ride-sourcing services. Proceedings of the 25th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2021: Sustainable Mobility, Hong Kong, December 9−10, 2021.
  • Zheng, Z., Yang, H., Wang, H., and Ke, J., 2019. The effect of bundle option in ride-sourcing markets on travel behavior. Proceedings of the 24th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2019: Transport and Smart Cities, Hong Kong, December 14−16, 2019.
  • Ke, J., Yang, H., and Zheng, Z., 2019. Equilibrium properties of on-demand ride-splitting markets in the presence of congestion effects. Proceedings of the 24th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2019: Transport and Smart Cities, Hong Kong, December 14−16, 2019.
  • Yang, H., Hassan, R., and Ke, J., 2019. Meeting points in ridesharing system. Proceedings of the 24th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2019: Transport and Smart Cities, Hong Kong, December 14−16, 2019.
  • Yao, H., Wu, F., Ke, J., Tang, X., Jia, Y., Lu, S., Gong, P., and Ye, J., 2018. Deep multi-view spatial temporal network for taxi demand prediction. Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), New Orleans, United States, Feb, 2018.
  • Yang, H., Qin, X., and Ke, J.*, 2018. Modelling and optimizing the real-time matching processes in a ride-sourcing market. Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018: Transportation Systems in the Connected Era, Hong Kong, December 8−10.
  • Ke, J., Cen, X., Yang, H., and Chen, X., 2018. Modelling the working and recharging schedules of electric-vehicle drivers in a ride-sourcing market. Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018: Transportation Systems in the Connected Era, Hong Kong, December 8−10.
  • Chen T., Liu J., Feng S., Ke J., 2024. A Top-to-Bottom Reposition Method for Ride-hailing Platforms. Presented in the Conference in Emerging Technologies in Transportation Systems (TRC-30), Crete, Greece, September 2–4, 2024.
  • Chen W. and Ke J.*, 2024. Joint pricing, matching, and repositioning for dynamic high-capacity ride-sharing considering future opportunity cost. Presented in the 2024 Institute for Operations Research and the Management Sciences (INFORMS) Annual Meeting, Seattle, Washington, United States, October 20–23, 2024.
  • Chen W., Ke J.*, and Chen X., 2024. Quantifying Carbon Emission Reductions from High-capacity Ride-sharing Services. Presented in the 13th Asia-Pacific Conference on Transportation and the Environment, Singapore, July 8–10, 2024.
  • Zhang K., Ke J.*, Wang H., and Yin Y, 2024. Operational strategy designs for on-demand food delivery services. Presented in the 103th Annual Meeting of Transportation Research Board, Washington DC, United States, January 7–11, 2024.
  • Zhang K. and Ke J.*, 2024. A three-sided network equilibrium model for on-demand food delivery services. Presented in the 103th Annual Meeting of Transportation Research Board, Washington DC, United States, January 7–11, 2024.
  • Chen W., Ke J.*, and Chen X, 2024. Quantifying traffic emission reductions and traffic congestion alleviation from high-capacity ride-sharing. Presented in the 103th Annual Meeting of Transportation Research Board, Washington DC, United States, January 7–11, 2024.
  • Wang C., and Ke J.*, 2024. Modelling a Ride-sourcing Market with a Third-Party Platform Integrator under Batch Matching Mechanisms. Presented in the 103th Annual Meeting of Transportation Research Board, Washington DC, United States, January 7–11, 2024.
  • Liang J., Ke J.*, Wang H., Ye H., and Tang J, 2023. A Poisson-Based Distribution Learning Framework for Short-Term Prediction of Food Delivery Demand Ranges. Presented in the 102th Annual Meeting of Transportation Research Board, Washington DC, United States, January 8–12, 2023.
  • Feng S., Ke, J. (speaker), Yang H., 2023. A comprehensive simulation platform for ride-sourcing markets: modules and functions. Presented in the 23rd COTA International Conference of Transportation Professionals (CICTP 2023), Beijing, China, July 14−17, 2023.
  • Feng S., Ke, J. (speaker), Yang H., 2023. A multi-functional simulation platform for ride-hailing service operations. Presented in the 5th International Symposium on Multimodal Transportation, Dalian, China, July 19−20, 2023.
  • Liang J., Ke, J. (speaker), 2023. Understanding users’ cancellation behaviors in online food delivery markets: a reference-dependent survival analysis, Presented in the World Transport Convention 2023, Wuhan, China, June 14−17, 2023.
  • Ke, J. (speaker), 2023. Simulation, Optimization and Artificial Intelligence for on-demand ride. Presented in the 13th POMS-HK Chapter International Conference, Hong Kong, China, January 7−8, 2023.
  • Li, X., Ke, J.* (speaker), Yang, H., Wang, H., Zhou, Y., 2021. A general matching function for ride-sourcing services. Presented in the 12th POMS-HK Chapter International Conference, Hong Kong, China, January 8−9, 2022. (Virtual mode)
  • Zhou, Y., Yang, H., Ke, J.* (speaker), Wang, H., and Li, X., 2021. Competitive ride-sourcing market with a third-party integrator. Presented in the 20th and 21st Joint COTA International Conference of Transportation Professionals, Xi’an, China, December 17−20, 2021. (Virtual mode)
  • Ke, J. (speaker), 2021. Pareto-efficient solutions and regulations of ride-sourcing markets. Presented in the 12th International Workshop on Computational Transportation Science (CTS), Harbin, China, July 28−29, 2021.
  • Ke, J. (speaker), 2021. Ride-hailing Demand Prediction Via Spatial-Temporal Multi-Graph Convolutional Neural Networks. Presented in the 2021 International Symposium on Transportation Data & Modelling (ISTDM), University of Michigan, United States, June 21−24, 2021. (Virtual mode)
  • Ke, J. (speaker), 2021. Online Optimization and Offline Learning for On-Demand Matching in Ride-Sourcing Services. Presented in the 2021 International Symposium on Transportation Data & Modelling (ISTDM), University of Michigan, United States, June 21−24, 2021. (Virtual mode)
  • Ke, J.* (speaker), Yang, H., and Zheng, Z., 2019. Modelling a ride-sharing market with congestion externality. Presented in the 3rd International Symposium on Multimodal Transportation (ISMT): Automation, Sharing, and Electrification in Transportation, National University of Singapore, Singapore, December 6−7, 2019.
  • Ke, J. (speaker), Cen, X., Yang, H., and Chen, X.*, 2019. Modelling the Working and recharging schedules of electric-vehicle drivers in a ride-sourcing market. Presented in the 98th Annual Meeting of Transportation Research Board, Washington DC, United States, January 13−17, 2019.
  • Ke, J.* (speaker), Yang, H., Li, X., and Wang, H., 2019. Pricing, matching probability, and detour cost in a ride-sharing market. Presented in the 98th Annual Meeting of Transportation Research Board, Washington DC, United States, January 13−17, 2019.
  • Ke, J. (speaker), Yang, H., Li, X., Wang, H.*, and Ye, J., 2019. Pricing and matching frictions in ride-sourcing markets. Presented in the 19th COTA International Conference of Transportation and Professionals, Nanjing, China, July 6−8, 2019.
  • Ke, J.* (speaker), Yang, H., and Zheng, Z., 2019. Can ride-splitting reduce traffic congestion? Presented in the 7th Informs Transportation Science & Logistic (TSL) Society Workshop, University of Vienna, Vienna, Austria, July 15−18, 2019.
  • Ke, J., 2020, Supply and Demand Management of Ride-sourcing Markets, Ph.D. Thesis, The Hong Kong University of Science and Technology, Hong Kong
  • Ke, J. et al., System and method for determining passenger-seeking ride-sourcing vehicle navigation. U.S. Patent, No. US 11,094,028 B2.
  • Ke, J. et al., A regional approach for predicting ride-hailing supply-demand gap(一种地理区域内网约车供需缺口预测方法). Chinese invention patent, No. CN109948822A.
  • Ke, J., Chen T., and Wang, J., An AI-based system for simulating a transportation network. U.S. Patent, Application No. 63/669,387, filed on 10 Jul 2024.