| 09:00-09:10 |
Opening |
Opening and Welcome |
| 09:10-09:50 |
Keynote 1 |
Prof. Lexing Xie |
| 09:50-10:30 |
Keynote 2 |
Dr. Chang Xu |
| 10:30-11:00 |
Break |
Coffee Break |
| 11:00-12:30 |
Session 1 |
Session 1: Six Full Paper Presentations
GraphSTAGE: Channel-Preserving Graph Neural Networks for Time Series Forecasting
DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs
Work Smarter, Not Harder: Towards An Efficient and Effective En Route Travel Time Estimation Framework
GRL4AOI: Graph-based Reinforement Learning for Service-aware AOI Segmentation
Unveiling Concept Shift via Spatio-Temporal State Learning
STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis
|
| 13:30-14:10 |
Keynote 3 |
Dr. Mingyue Cheng |
| 14:10-15:00 |
Keynote 4 |
Dr. Zhengyang Zhou |
| 15:00-15:30 |
Break |
Coffee Break |
| 15:30-16:15 |
Session 2 |
Session 2: Three Full Paper Presentations
Mitigating Spatial Disparity in Urban Prediction Using Residual-Aware Spatiotemporal Graph Neural Networks: A Chicago Case Study
House Price Prediction Using Conditional Neural Networks
A Competitive-Cooperative Approach to Dynamic Pricing for Two-Sided Hospitality Platforms
|
| 16:15-16:45 |
Short Papers |
Short Paper Presentations
A Spatial-temporal Deep Probabilistic Diffusion Model for Reliable Hail Nowcasting with Radar Echo Extrapolation
Fine-grained Temporal Learning in Traffic Flow Forecasting: The Power of Intraday Patterns
Efficient Epidemic Intervention Generation: A Graph Adversarial Attack Perspective
|
| 16:45-17:00 |
Closing |
Award Ceremony & Closing |