Inductive Graph Neural Networks for Spatiotemporal Kriging. - Yuankai Wu; Dingyi Zhuang; Aurélie Labbe; Lijun Sun 001 (AAAI, 2021)

Spatial Aggregation and Temporal Convolution Networks for Real-time Kriging. - Yuankai Wu; Dingyi Zhuang; Mengying Lei; Aurélie Labbe; Lijun Sun 001 (CoRR, 2021)

The Braess's Paradox in Dynamic Traffic. - Dingyi Zhuang; Yuzhu Huang; Vindula Jayawardana; Jinhua Zhao; Dajiang Suo; Cathy Wu 002 (ITSC, 2022)

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

The Braess Paradox in Dynamic Traffic. - Dingyi Zhuang; Yuzhu Huang; Vindula Jayawardana; Jinhua Zhao; Dajiang Suo; Cathy Wu 002 (CoRR, 2022)

A Universal Framework of Spatiotemporal Bias Block for Long-Term Traffic Forecasting. - Fuqiang Liu; Jiawei Wang 005; Jingbo Tian; Dingyi Zhuang; Luis Miranda-Moreno; Lijun Sun 001 (IEEE Trans. Intell. Transp. Syst., 2022)

Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction. - Xinke Jiang; Dingyi Zhuang; Xianghui Zhang; Hao Chen 103; Jiayuan Luo; Xiaowei Gao (CIKM, 2023)

Uncertainty Quantification in the Road-Level Traffic Risk Prediction by Spatial-Temporal Zero-Inflated Negative Binomial Graph Neural Network(STZINB-GNN) (Short Paper). - Xiaowei Gao; James Haworth; Dingyi Zhuang; Huanfa Chen; Xinke Jiang (GIScience, 2023)

ST-GIN: An Uncertainty Quantification Approach in Traffic Data Imputation with Spatio-Temporal Graph Attention and Bidirectional Recurrent United Neural Networks. - Zepu Wang; Dingyi Zhuang; Yankai Li; Jinhua Zhao; Peng Sun 007; Shenhao Wang; Yulin Hu (ITSC, 2023)

Fairness-enhancing deep learning for ride-hailing demand prediction. - Yunhan Zheng; Qingyi Wang; Dingyi Zhuang; Shenhao Wang; Jinhua Zhao (CoRR, 2023)

ST-GIN: An Uncertainty Quantification Approach in Traffic Data Imputation with Spatio-temporal Graph Attention and Bidirectional Recurrent United Neural Networks. - Zepu Wang; Dingyi Zhuang; Yankai Li; Jinhua Zhao; Peng Sun 007 (CoRR, 2023)

Uncertainty Quantification in the Road-level Traffic Risk Prediction by Spatial-Temporal Zero-Inflated Negative Binomial Graph Neural Network(STZINB-GNN). - Xiaowei Gao; James Haworth; Dingyi Zhuang; Huanfa Chen; Xinke Jiang (CoRR, 2023)

Spatiotemporal Graph Neural Networks with Uncertainty Quantification for Traffic Incident Risk Prediction. - Xiaowei Gao; Xinke Jiang; Dingyi Zhuang; Huanfa Chen; Shenhao Wang; James Haworth (CoRR, 2023)

Large Language Models for Travel Behavior Prediction. - Baichuan Mo; Hanyong Xu; Dingyi Zhuang; Ruoyun Ma; Xiaotong Guo; Jinhua Zhao (CoRR, 2023)

Low-Rank Hankel Tensor Completion for Traffic Speed Estimation. - Xudong Wang; Yuankai Wu; Dingyi Zhuang; Lijun Sun 001 (IEEE Trans. Intell. Transp. Syst., 2023)

ItiNera: Integrating Spatial Optimization with Large Language Models for Open-domain Urban Itinerary Planning. - Yihong Tang; Zhaokai Wang; Ao Qu; Yihao Yan; Zhaofeng Wu; Dingyi Zhuang; Jushi Kai; Kebing Hou; Xiaotong Guo; Jinhua Zhao; Zhan Zhao; Wei Ma (EMNLP (Industry Track), 2024)

SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks. - Dingyi Zhuang; Yuheng Bu; Guang Wang 001; Shenhao Wang; Jinhua Zhao (SIGSPATIAL/GIS, 2024)

Fairness-Enhancing Vehicle Rebalancing in the Ride-hailing System. - Xiaotong Guo; Hanyong Xu; Dingyi Zhuang; Yunhan Zheng; Jinhua Zhao (CoRR, 2024)

Timeseries Suppliers Allocation Risk Optimization via Deep Black Litterman Model. - Jiayuan Luo; Wentao Zhang 008; Yuchen Fang 001; Xiaowei Gao; Dingyi Zhuang; Hao Chen 103; Xinke Jiang (CoRR, 2024)

Synergizing Spatial Optimization with Large Language Models for Open-Domain Urban Itinerary Planning. - Yihong Tang; Zhaokai Wang; Ao Qu; Yihao Yan; Kebing Hou; Dingyi Zhuang; Xiaotong Guo; Jinhua Zhao; Zhan Zhao; Wei Ma (CoRR, 2024)

Advancing Transportation Mode Share Analysis with Built Environment: Deep Hybrid Models with Urban Road Network. - Dingyi Zhuang; Qingyi Wang; Yunhan Zheng; Xiaotong Guo; Shenhao Wang; Haris N. Koutsopoulos; Jinhua Zhao (CoRR, 2024)

Sparkle: Mastering Basic Spatial Capabilities in Vision Language Models Elicits Generalization to Composite Spatial Reasoning. - Yihong Tang; Ao Qu; Zhaokai Wang; Dingyi Zhuang; Zhaofeng Wu; Wei Ma; Shenhao Wang; Yunhan Zheng; Zhan Zhao; Jinhua Zhao (CoRR, 2024)

Uncertainty Quantification of Spatiotemporal Travel Demand With Probabilistic Graph Neural Networks. - Qingyi Wang; Shenhao Wang; Dingyi Zhuang; Haris N. Koutsopoulos; Jinhua Zhao (IEEE Trans. Intell. Transp. Syst., 2024)

Time Series Supplier Allocation via Deep Black-Litterman Model. - Xinke Jiang; Wentao Zhang 008; Yuchen Fang 001; Xiaowei Gao; Hao Chen 103; Haoyu Zhang; Dingyi Zhuang; Jiayuan Luo (AAAI, 2025)

GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks. - Dingyi Zhuang; Chonghe Jiang; Yunhan Zheng; Shenhao Wang; Jinhua Zhao (ICLR, 2025)

Mitigating Spatial Disparity in Urban Prediction Using Residual-Aware Spatiotemporal Graph Neural Networks: A Chicago Case Study. - Dingyi Zhuang; Hanyong Xu; Xiaotong Guo; Yunhan Zheng; Shenhao Wang; Jinhua Zhao (WWW (Companion Volume), 2025)

Virtual Nodes Improve Long-term Traffic Prediction. - Xiaoyang Cao; Dingyi Zhuang; Jinhua Zhao; Shenhao Wang (CoRR, 2025)

Reimagining Urban Science: Scaling Causal Inference with Large Language Models. - Yutong Xia; Ao Qu; Yunhan Zheng; Yihong Tang; Dingyi Zhuang; Yuxuan Liang; Cathy Wu 002; Roger Zimmermann; Jinhua Zhao (CoRR, 2025)

Generative AI for Urban Design: A Stepwise Approach Integrating Human Expertise with Multimodal Diffusion Models. - Mingyi He; Yuebing Liang; Shenhao Wang; Yunhan Zheng; Qingyi Wang; Dingyi Zhuang; Li Tian; Jinhua Zhao (CoRR, 2025)

Interpretable Time Series Autoregression for Periodicity Quantification. - Xinyu Chen; Vassilis Digalakis Jr; Lijun Ding; Dingyi Zhuang; Jinhua Zhao (CoRR, 2025)