Large-scale short-term urban taxi demand forecasting using deep learning. - Siyu Liao; Liutong Zhou; Xuan Di; Bo Yuan 001; Jinjun Xiong (ASP-DAC, 2018)

Multimodal Connections between Dockless Bikesharing and Ride-Hailing: An Empirical Study in New York City. - Qi Luo; Xuechun Dou; Xuan Di; Robert Cornelius Hampshire (ITSC, 2018)

Stabilizing Traffic via Autonomous Vehicles: A Continuum Mean Field Game Approach. - Kuang Huang; Xuan Di; Qiang Du 001; Xi Chen (ITSC, 2019)

A Game-Theoretic Framework for Autonomous Vehicles Velocity Control: Bridging Microscopic Differential Games and Macroscopic Mean Field Games. - Kuang Huang; Xuan Di; Qiang Du 001; Xi Chen (CoRR, 2019)

Where to Find Next Passengers on E-hailing Platforms? - A Markov Decision Process Approach. - Zhenyu Shou; Xuan Di; Jieping Ye; Hongtu Zhu; Robert C. Hampshire (CoRR, 2019)

Liability Design for Autonomous Vehicles and Human-Driven Vehicles: A Hierarchical Game-Theoretic Approach. - Xuan Di; Xu Chen 033; Eric Talley (CoRR, 2019)

A Similitude Theory for Modeling Traffic Flow Dynamics. - Xuan Di; Yan Zhao 011; Shihong Ed Huang; Henry X. Liu (IEEE Trans. Intell. Transp. Syst., 2019)

Similarity Analysis of Spatial-Temporal Mobility Patterns for Travel Mode Prediction Using Twitter Data. - Zhenyu Shou; Zhenhao Cao; Xuan Di (ITSC, 2020)

Long-Term Prediction of Lane Change Maneuver Through a Multilayer Perceptron. - Zhenyu Shou; Ziran Wang; Kyungtae Han; Yongkang Liu 005; Prashant Tiwari; Xuan Di (IV, 2020)

An LSTM-Based Autonomous Driving Model Using Waymo Open Dataset. - Zhicheng Li; Zhihao Gu; Xuan Di; Rongye Shi (CoRR, 2020)

Reward Design for Driver Repositioning Using Multi-Agent Reinforcement Learning. - Zhenyu Shou; Xuan Di (CoRR, 2020)

When Do Drivers Concentrate? Attention-based Driver Behavior Modeling With Deep Reinforcement Learning. - Xingbo Fu; Xuan Di; Zhaobin Mo (CoRR, 2020)

A Survey on Autonomous Vehicle Control in the Era of Mixed-Autonomy: From Physics-Based to AI-Guided Driving Policy Learning. - Xuan Di; Rongye Shi (CoRR, 2020)

Multi-Agent Reinforcement Learning for Dynamic Routing Games: A Unified Paradigm. - Zhenyu Shou; Xuan Di (CoRR, 2020)

Driving and Routing Game for Autonomous Vehicles on a Network. - Kuang Huang; Xu Chen; Xuan Di; Qiang Du 001 (CoRR, 2020)

A Physics-Informed Deep Learning Paradigm for Car-Following Models. - Zhaobin Mo; Xuan Di; Rongye Shi (CoRR, 2020)

A restricted path-based ridesharing user equilibrium. - Meng Li; Xuan Di; Henry X. Liu; Hai-Jun Huang (J. Intell. Transp. Syst., 2020)

Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models. - Rongye Shi; Zhaobin Mo; Xuan Di (AAAI, 2021)

Sentiment Analysis of Autonomous Vehicles After Extreme Events Using Social Media Data. - Xu Chen 033; Haohan Zeng; Heng Xu; Xuan Di (ITSC, 2021)

Physics-Informed Deep Learning for Traffic State Estimation. - Rongye Shi; Zhaobin Mo; Kuang Huang; Xuan Di; Qiang Du 001 (CoRR, 2021)

CVLight: Deep Reinforcement Learning for Adaptive Traffic Signal Control with Connected Vehicles. - Wangzhi Li; Yaxing Cai; Ujwal Dinesha; Yongjie Fu; Xuan Di (CoRR, 2021)

A Physics-Informed Deep Learning Paradigm for Traffic State Estimation and Fundamental Diagram Discovery. - Rongye Shi; Zhaobin Mo; Kuang Huang; Xuan Di; Qiang Du 001 (CoRR, 2021)

Learning Human Driving Behaviors with Sequential Causal Imitation Learning. - Kangrui Ruan; Xuan Di (AAAI, 2022)

How the COVID-19 Pandemic Influences Human Mobility? Similarity Analysis Leveraging Social Media Data. - Xu Chen 033; Xuan Di (ITSC, 2022)

SMART-eFlo: An Integrated SUMO-Gym Framework for Multi-Agent Reinforcement Learning in Electric Fleet Management Problem. - Shuo Liu 018; Yunhao Wang; Xu Chen 033; Yongjie Fu; Xuan Di (ITSC, 2022)

Quantifying Uncertainty In Traffic State Estimation Using Generative Adversarial Networks. - Zhaobin Mo; Yongjie Fu; Xuan Di (ITSC, 2022)

Bayesian Optimization for Multi-Agent Routing in Markov Games. - Zhenyu Shou; Xu Chen 033; Xuan Di (ITSC, 2022)

Social Learning In Markov Games: Empowering Autonomous Driving. - Xu Chen 033; Zechu Li; Xuan Di (IV, 2022)

TrafficFlowGAN: Physics-Informed Flow Based Generative Adversarial Network for Uncertainty Quantification. - Zhaobin Mo; Yongjie Fu; Daran Xu; Xuan Di (ECML/PKDD (3), 2022)

A Unified Network Equilibrium for E-Hailing Platform Operation and Customer Mode Choice. - Xu Chen; Xuan Di (CoRR, 2022)

A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation. - Rongye Shi; Zhaobin Mo; Kuang Huang; Xuan Di; Qiang Du 001 (IEEE Trans. Intell. Transp. Syst., 2022)

A Hybrid Framework of Reinforcement Learning and Physics-Informed Deep Learning for Spatiotemporal Mean Field Games. - Xu Chen 033; Shuo Liu 018; Xuan Di (AAMAS, 2023)

Learning Dual Mean Field Games on Graphs. - Xu Chen 033; Shuo Liu 018; Xuan Di (ECAI, 2023)

Causal Imitation Learning via Inverse Reinforcement Learning. - Kangrui Ruan; Junzhe Zhang 001; Xuan Di; Elias Bareinboim (ICLR, 2023)

Whose Attitudes Toward Transit Are Most Affected by Rising Subway Crimes in New York City? - Xu Chen 033; Yishi Wang; Xuan Di (ITSC, 2023)

Federated Reinforcement Learning for Adaptive Traffic Signal Control: A Case Study in New York City. - Yongjie Fu; Xuan Di (ITSC, 2023)

Detecting mild cognitive impairment and dementia in older adults using naturalistic driving data and interaction-based classification from influence score. - Xuan Di; Yiqiao Yin; Yongjie Fu; Zhaobin Mo; Shaw-Hwa Lo; Carolyn DiGuiseppi; David W. Eby; Linda L. Hill; Thelma J. Mielenz; David Strogatz; Minjae Kim; Guohua Li (Artif. Intell. Medicine, 2023)

Systemic reliability of bridge networks with mobile sensing-based model updating for postevent transportation decisions. - Ekin Ozer; Arman Malekloo; Wasim Ramadan; Thanh T. X. Tran; Xuan Di (Comput. Aided Civ. Infrastructure Eng., 2023)

Social Learning for Sequential Driving Dilemmas. - Xu Chen 033; Xuan Di; Zechu Li (Games, 2023)

Robust Data Sampling in Machine Learning: A Game-Theoretic Framework for Training and Validation Data Selection. - Zhaobin Mo; Xuan Di; Rongye Shi (Games, 2023)

Sentiment Analysis on Multimodal Transportation during the COVID-19 Using Social Media Data. - Xu Chen 033; Zihe Wang; Xuan Di (Inf., 2023)

Physics-Informed Deep Learning for Traffic State Estimation: A Survey and the Outlook. - Xuan Di; Rongye Shi; Zhaobin Mo; Yongjie Fu (Algorithms, 2023)

PI-NeuGODE: Physics-Informed Graph Neural Ordinary Differential Equations for Spatiotemporal Trajectory Prediction. - Zhaobin Mo; Yongjie Fu; Xuan Di (AAMAS, 2024)

A Single Online Agent Can Efficiently Learn Mean Field Games. - Chenyu Zhang 002; Xu Chen 033; Xuan Di (ECAI, 2024)

SLAMuZero: Plan and Learn to Map for Joint SLAM and Navigation. - Bowen Fang; Xu Chen 033; Zhengkun Pan; Xuan Di (ICAPS, 2024)

Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm. - Fuzhong Zhou; Chenyu Zhang 002; Xu Chen 033; Xuan Di (ICML, 2024)

GenDDS: Generating Diverse Driving Video Scenarios with Prompt-to-Video Generative Model. - Yongjie Fu; Yunlong Li; Xuan Di (ITSC, 2024)

Comparative Studies of Neural Operators For Traffic State Estimation. - Qi Gao; Xuan Di (ITSC, 2024)

SafeAug: Safety-Critical Driving Data Augmentation from Naturalistic Datasets. - Yunlong Li; Zhaobin Mo; Xuan Di (ITSC, 2024)

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs. - Zhaobin Mo; Qingyuan Liu; Baohua Yan; Longxiang Zhang; Xuan Di (ITSC, 2024)

From Twitter to Reasoner: Understand Mobility Travel Modes and Sentiment Using Large Language Models. - Kangrui Ruan; Xinyang Wang; Xuan Di (ITSC, 2024)

Digital Twin for Pedestrian Safety Warning at a Single Urban Traffic Intersection. - Yongjie Fu; Mehmet Kerem Türkcan; Vikram Anantha; Zoran Kostic; Gil Zussman; Xuan Di (IV, 2024)

Causal Imitation for Markov Decision Processes: a Partial Identification Approach. - Kangrui Ruan; Junzhe Zhang 001; Xuan Di; Elias Bareinboim (NeurIPS, 2024)

Learn to Tour: Operator Design For Solution Feasibility Mapping in Pickup-and-delivery Traveling Salesman Problem. - Bowen Fang; Xu Chen 033; Xuan Di (CoRR, 2024)

TraveLLM: Could you plan my new public transit route in face of a network disruption? - Bowen Fang; Zixiao Yang; Shukai Wang; Xuan Di (CoRR, 2024)

Can LLMs Understand Social Norms in Autonomous Driving Games? - Boxuan Wang; Haonan Duan 003; Yanhao Feng; Xu Chen 033; Yongjie Fu; Zhaobin Mo; Xuan Di (CoRR, 2024)

DriveGenVLM: Real-world Video Generation for Vision Language Model based Autonomous Driving. - Yongjie Fu; Anmol Jain; Xuan Di; Xu Chen 033; Zhaobin Mo (CoRR, 2024)

A Game-Theoretic Framework for Generic Second-Order Traffic Flow Models Using Mean Field Games and Adversarial Inverse Reinforcement Learning. - Zhaobin Mo; Xu Chen 033; Xuan Di; Elisa Iacomini; Chiara Segala; Michael Herty; Mathieu Laurière (Transp. Sci., 2024)

Cross- and Context-Aware Attention Based Spatial-Temporal Graph Convolutional Networks for Human Mobility Prediction. - Zhaobin Mo; Haotian Xiang; Xuan Di (ACM Trans. Spatial Algorithms Syst., 2024)

Mobility Pattern Analysis during Russia-Ukraine War Using Twitter Location Data. - Yupei Shu; Xu Chen 033; Xuan Di (Inf., 2024)

Physics-Informed Graph Neural Operator for Mean Field Games on Graph: A Scalable Learning Approach. - Xu Chen 033; Shuo Liu 018; Xuan Di (Games, 2024)

InfoSTGCAN: An Information-Maximizing Spatial-Temporal Graph Convolutional Attention Network for Heterogeneous Human Trajectory Prediction. - Kangrui Ruan; Xuan Di (Comput., 2024)

Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation. - Chenyu Zhang 002; Xu Chen 033; Xuan Di (ICLR, 2025)

Special Issue on Machine Learning Methods for Urban Passenger Mobility. - Xuan Di; Sean Qian; Carolina Osorio (Transp. Sci., 2025)

diffIRM: A Diffusion-Augmented Invariant Risk Minimization Framework for Spatiotemporal Prediction over Graphs. - Zhaobin Mo; Haotian Xiang; Xuan Di (Transp. Sci., 2025)

AI-Powered Urban Transportation Digital Twin: Methods and Applications. - Xuan Di; Yongjie Fu; Mehmet Kerem Türkcan; Mahshid Ghasemi; Zhaobin Mo; Chengbo Zang; Abhishek Adhikari; Zoran Kostic; Gil Zussman (CoRR, 2025)

Federated Hierarchical Reinforcement Learning for Adaptive Traffic Signal Control. - Yongjie Fu; Lingyun Zhong; Zifan Li; Xuan Di (CoRR, 2025)

Generative AI for Autonomous Driving: Frontiers and Opportunities. - Yuping Wang; Shuo Xing; Cui Can; Renjie Li 003; Hongyuan Hua; Kexin Tian; Zhaobin Mo; Xiangbo Gao; Keshu Wu; Sulong Zhou; Hengxu You; Juntong Peng; et al. (CoRR, 2025)

LLM-based Realistic Safety-Critical Driving Video Generation. - Yongjie Fu; Ruijian Zha; Pei Tian; Xuan Di (CoRR, 2025)