Publications

Grouped by research theme, newest first within each theme. ✉ denotes the corresponding author and † equal contribution. A full list is also available on Google Scholar.

Papers 13 entries

Learning-based Decision Making and Optimization for Mobility Systems

  • D<sup>3</sup>-Subsidy: Online and Sequential Driver Subsidy Decision-Making for Large-Scale Ride-Hailing Market
    Ride-HailingSequential Decision MakingSubsidy Control

    D3-Subsidy: Online and Sequential Driver Subsidy Decision-Making for Large-Scale Ride-Hailing Market

    Chen, T., Su, R., Feng, S., Zhang, L., Zhang, H., Wang, H., Ma, Z., Ke, J., & Ma, L.

    Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Vol. 2 (KDD '26), pp. 7094–7105, 2026.

    CCF-A
    Paper DOI
  • T2BR: A Hierarchical Repositioning Approach for Autonomous Mobility-on-Demand Systems
    Autonomous Mobility-on-DemandReinforcement LearningFleet Repositioning

    T2BR: A Hierarchical Repositioning Approach for Autonomous Mobility-on-Demand Systems

    Chen, T., Liu, J., Feng, S.✉, Qiu, J., & Ke, J.

    IEEE Transactions on Intelligent Transportation Systems, 26(12), 23139–23150, 2025.

    SCI-Q1 Top CCF-B IF 8.5
    Paper
  • IEEE TITS
    Ride-HailingConstrained OptimizationSubsidy Control

    Sequential Driver Subsidy Control for Large-Scale Ride-Hailing Platforms under Budget Constraints

    Chen, T., Su, R., Feng, S.✉, Zhang, L., Wang, H., Liu, X., Zhang, H., Ma, Z., Ma, L., & Ke, J.✉

    IEEE Transactions on Intelligent Transportation Systems.

    Under review
  • Dynamic Matching Radius Decision Model for On-Demand Ride Services: A Deep Multi-Task Learning Approach
    Ride-HailingMulti-Task LearningOrder Matching

    Dynamic Matching Radius Decision Model for On-Demand Ride Services: A Deep Multi-Task Learning Approach

    Chen, T., Shen, Z., Feng, S.✉, Yang, L., & Ke, J.

    Transportation Research Part E: Logistics and Transportation Review, 193, 103822, 2025.

    SCI-Q1 Top IF 8.3
    Paper Code
  • TR Part E
    Multimodal RoutingDeep LearningUser Preference

    Multipath: Deep Learning-Based Multimodal Route Guidance with User Preference Integration

    Shen, Z., Chen, T., Zhou, B., & Ke, J.✉

    Transportation Research Part E: Logistics and Transportation Review.

    Major revision

Foundation Models and LLMs for Urban Computing

  • Addressing the Online Incremental Transport Mode Choice Prediction Problem with an LLM-Augmented Class-Incremental Learning Approach
    LLM AugmentationTravel BehaviourContinual Learning

    Addressing the Online Incremental Transport Mode Choice Prediction Problem with an LLM-Augmented Class-Incremental Learning Approach

    Chen, T., Shen, Z., Zhou, B., Liu, Y., Wang, S., & Ke, J.

    Transportation Research Part C: Emerging Technologies, 188, 105709, 2026.

    SCI-Q1 Top IF 7.9
    Paper
  • TBS
    LLM AgentsFeature DiscoveryTravel Behaviour

    Assisting Feature Discovery for Travel-Behaviour Regression with Iterative Large Language Model Agents

    Chen, T.†, Su, R.†, Zhao, Y.✉, & Ke, J.

    Travel Behaviour and Society.

    Under review
  • Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models
    LLM ReasoningPrompt Design

    Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models

    Tan, W., Chen, D., Xue, J., Wang, Z., & Chen, T.✉

    Proceedings of the 31st International Conference on Computational Linguistics: Industry Track (COLING), pp. 827–839, 2025.

    CCF-B
    Paper arXiv Code
  • AAAI 2027
    Vision-Language ModelsAutonomous Taxi Fleets

    VISTA: Vision-Language Integrated Spatiotemporal Station Recommendation for Autonomous Taxi Fleets

    Jiang, Z., Chen, T., Xu, J., Shen, Z., Zhou, B., & Ke, J.

    AAAI Conference on Artificial Intelligence (AAAI).

    Under review
  • AAAI 2027
    LLM AugmentationBayesian NetworksTabular Generation

    LAB-Tab: LLM-Augmented Bayesian Network Adaptation for Few-Shot Tabular Generation

    Shen, Z., Chen, T., Zhou, B., Jiang, Z., & Ke, J.✉

    AAAI Conference on Artificial Intelligence (AAAI).

    Under review
    arXiv

Human Mobility Intelligence and Behavioural Modelling

  • To Grab or Not to Grab? Revealing Determinants of Drivers' Willingness to Grab Orders under the Broadcasting Mode
    Driver BehaviourRide-HailingBroadcasting Mode

    To Grab or Not to Grab? Revealing Determinants of Drivers' Willingness to Grab Orders under the Broadcasting Mode

    Chen, T., Liang, J., Zhao, Y.✉, & Ke, J.

    Travel Behaviour and Society, 41, 101093, 2025.

    SSCI-Q1 Top IF 5.1
    Paper

AI-enabled Transportation Simulation and Digital Twins

  • A Multi-Functional Simulation Platform for On-Demand Ride Service Operations
    Simulation PlatformOpen SourceRide-Sourcing

    A Multi-Functional Simulation Platform for On-Demand Ride Service Operations

    Feng, S., Chen, T., Zhang, Y., Ke, J.✉, Zheng, Z., & Yang, H.

    Communications in Transportation Research, 4, 100141, 2024.

    SCI-Q1 Top IF 12.5
    Paper Code Video
  • Preprint
    SimulationDigital TwinMultimodal Transport

    SMARTSim: Scalable Multimodal AI-Friendly Rapid Transportation Simulator

    Wang, J., Chen, T., & Ke, J.✉

    Engineering Management.

    Major revision

Conference Presentations

  • Enhancing Autonomous Mobility-on-Demand Systems: A Hierarchical Repositioning Approach Integrating Regional-level and Route-level Decisions

    Chen, T., Liu, J., Feng, S.✉, Ke, J.

    Transportation Research Board (TRB) 99th Annual Meeting, Washington, DC, USA Jan 2025

  • A Top-to-Bottom Repositioning Method for Ride-Hailing Platforms

    Chen, T.✉, Liu, J., Feng, S., Ke, J.

    Conference in Emerging Technologies in Transportation Systems (TRC-30), Crete, Greece Sep 2024

  • A Top-to-Bottom Repositioning Method for Ride-Hailing Platforms

    Chen, T.✉, Liu, J., Hu, Z., Feng, S., Ke, J.

    28th International Conference of the Hong Kong Society for Transportation Studies (HKSTS), Hong Kong Dec 2024

  • To Grab or Not to Grab? Revealing Determinants of Drivers' Willingness to Grab Orders under the Broadcasting Mode

    Chen, T.✉, Liang, J., Zhao, Y., Ke, J.

    28th International Conference of the Hong Kong Society for Transportation Studies (HKSTS), Hong Kong Dec 2024

  • TEB: A Time-Series Model for On-Demand E-Hailing Matching in the Broadcasting Mode

    Chen, T.✉, Shen, Z., Feng, S., Ke, J.

    27th International Conference of the Hong Kong Society for Transportation Studies (HKSTS), Hong Kong Dec 2023

Patents

  • An AI-based System for Simulating a Transportation Network

    Ke, J., Chen, T., Wang, J.

    Hong Kong Standard Patent (Original Grant) 22025109703.0 Filed 10 Jul 2025
    Claiming priority to U.S. Patent Application No. 63/669,387.

  • 基于类别增量的可扩充出行选择预测系统

    An Expandable Travel Choice Prediction System Based on Class-Incremental Learning

    Ke, J., Chen, T.

    China Patent 2026105953942 Filed 30 Apr 2026

  • 一种用于管理出行服务的方法和装置

    A Method and Apparatus for Managing Mobility Services

    Chen, T., Zhang, L., Ma, L., Ma, Z., Wang, H., Feng, S., Su, R.

    China Patent Application 202610230692.1 Filed 26 Feb 2026

  • 一种用于管理出行服务的方法和装置

    A Method and Apparatus for Managing Mobility Services

    Su, R., Zhang, L., Ma, L., Ma, Z., Wang, H., Feng, S., Chen, T.

    China Patent Application 202610230690.2 Filed 26 Feb 2026

  • 基于行为感知的混合自动驾驶共享出行司乘匹配方法

    A Behaviour-Aware Driver–Passenger Matching Method for Mixed-Autonomy Shared Mobility

    Ke, J., Chen, T., Wang, J.

    China Patent Application 202511647569.1 Filed 11 Nov 2025

Software Copyrights

  • Teaching resource network management system based on knowledge graph No. 2021SR0651132
  • Teaching resource network making system based on knowledge graph No. 2021SR0651080
  • Teaching resource network display system based on knowledge graph No. 2021SR0651130